CBCL PUBLICATIONS BY YEAR

2012

Alvarez M., N. Lawrence, L. Rosasco. Kernels for Vector-Valued Functions: a Review.. Foundations and Trends in Machine Learning 4(3):195-266, 2012

Canas G. D., T. Poggio, L. Rosasco, Learning Manifolds with K-Means and K-Flats., Advances in Neural Information Processing Systems, Lake Tahoe, December 2012

Canas G. D., L. Rosasco, Learning Probability Measures with respect to Optimal Transport Metrics., Advances in Neural Information Processing Systems, Lake Tahoe, December 2012

Canas G. D., S. J. Gortler, Duals of Orphan-Free Anisotropic Voronoi Diagrams are Embedded Meshes., 28th ACM Symposium on Computational Geometry, 2012

Canas, G. D., Practical Conditions for Well-behaved-ness of Anisotropic Voronoi Diagrams., Arxiv 1202.0867

Isik, L.*, J.Z. Leibo* and T. Poggio, Learning and disrupting invariance in visual recognition with a temporal association rule. Front. Comput. Neurosci. 6:37. doi: 10.3389/fncom.2012.00037, June 25, 2012
*These authors contributed equally to this work.

Isik, L., E.M. Meyers, J.Z. Leibo, and T. Poggio, Preliminary MEG decoding results, MIT-CSAIL-TR-2012-010,CBCL-307, Massachusetts Institute of Technology, Cambridge, MA, April 20, 2012

Little A. V., M. Maggioni, and L. Rosasco Multiscale Geometric Methods for Data Sets I:Multiscale SVD, Noise and Curvature., MIT-CSAIL-TR-2012-029 ,CBCL-310, Massachusetts Institute of Technology, Cambridge, MA, September 2012

Meyers, E., X.L.Qi and C. Constantinidis, Incorporation of new information into prefrontal cortical activity after learning working memory tasks. Proceedings of the National Academy of Sciences, 109:4651-4656-8855, 2012.

Mroueh Y., T. Poggio, L. Rosasco, and J. J. Slotine Multi-class Learning with Simplex Coding., Advances in Neural Information Processing Systems, Lake Tahoe, December 2012

Poggio, T. The Levels of Understanding framework, revised, MIT-CSAIL-TR-2012-014, CBCL-308, Massachusetts Institute of Technology, Cambridge, MA, May 31, 2012

Poggio, T. The Levels of Understanding framework, revised. Perception, volume 41, pages 1017 - 1023, December 2012 doi:10.1068/p7299

Poggio T., J. Mutch, F. Anselmi, L. Rosasco, J.Z. Leibo, and A. Tacchetti, The computational magic of the ventral stream: sketch of a theory (and why some deep architectures work). MIT-CSAIL-TR-2012-035, Massachusetts Institute of Technology, Cambridge, MA, December 29, 2012.

Tacchetti, A., P. Mallapragada, M. Santoro, and L. Rosasco, GURLS: a Toolbox for Regularized Least Squares Learning, MIT-CSAIL-TR-2012-003, CBCL-306, Massachusetts Institute of Technology, Cambridge, MA, January, 2012
Previous version: GURLS: a Toolbox for Large Scale Multiclass Learning, Workshop: "Big Learning: Algorithms, Systems, and Tools for Learning at Scale" at NIPS 2011, December 16-17 2011, Sierra Nevada, Spain.

Tan, C., J.Z. Leibo, and T. Poggio, Throwing Down the Visual Intelligence Gauntlet. Machine Learning for Computer Vision; eds Cipolla R., Battiato S., Farinella G.M., Springer: Studies in Computational Intelligence Vol. 411. July, 2012.

2011:

Alvarez, M.A., L. Rosasco and N. D. Lawrence, Kernels for Vector-Valued Functions: a Review, MIT-CSAIL-TR-2011-033/CBCL-301 Massachusetts Institute of Technology, Cambridge, MA, June 30, 2011

Baldassarre, L., L. Rosasco, A. Barla, and A. Verri, Multi-Output Learning via Spectral Filtering, MIT-CSAIL-TR-2011-004/CBCL-296, Massachusetts Institute of Technology, Cambridge, MA, January 24, 2011

Chikkerur, S. and T. Poggio, Approximations in the HMAX Model, MIT-CSAIL-TR-2011-021/CBCL-298, Massachusetts Institute of Technology, Cambridge, MA, April 14, 2011

Dahan, E., A.J. Kim, A.W. Lo, T. Poggio, and N. Chan, Securities Trading of Concepts (STOC) Journal of Marketing Research: Vol. 48, No. 3, pp. 497-517., doi: 10.1509/jmkr.48.3.497, 2011

Isik, L., J.Z. Leibo, J. Mutch, S.W. Lee, and T Poggio, A hierarchical model of peripheral vision, MIT-CSAIL-TR-2011-031/CBCL-300, Massachusetts Institute of Technology, Cambridge, MA, June 2011

Isik, L., J.Z. Leibo and T. Poggio, Learning and disrupting invariance in visual recognition, MIT-CSAIL-TR-2011-040/CBCL-302, Massachusetts Institute of Technology, Cambridge, MA, September 10, 2011

Jhuang, H. (Ph.D. Thesis, EECS, MIT, March 2011): Dorsal Stream: From Algorithm to Neuroscience

Kuehne, T., H. Jhuang, E. Garrote, T. Poggio, and T. Serre, "HMDB: A Large Video Database for Human Motion Recognition," ICCV 2011, Click here for software documentation.

Leibo, J.Z., J. Mutch and T Poggio. How can cells in the anterior medial face patch be viewpoint invariant?, Presented at COSYNE 2011, Salt Lake City, UT. Available from Nature Precedings at dx.doi.org/10.1038/npre.2011.5845.1

Leibo, J.Z., J. Mutch andT Poggio, Learning to discount transformations as the computational goal of visual cortex, Presented at FGVC/CVPR 2011, Colorado Springs, CO. Available from Nature Precedings at dx.doi.org/10.1038/npre.2011.6078.1

Leibo, J.Z., Mutch J., and T. Poggio, Why The Brain Separates Face Recognition From Object Recognition, Advances in Neural Information Processing Systems, Granada Spain, December 2011

Meyers, E., Kreiman, G. Tutorial on Pattern Classification in Cell Recording. In: Visual population codes. Kreigeskorte, N., and Kreiman, G. (eds.), 2011, MIT Press.

Mosci, S., L Rosasco, M. Santoro, A. Verri, and S. Villa, Nonparametric Sparsity and Regularization, MIT-CSAIL-TR-2011-041/CBCL-303 Massachusetts Institute of Technology, Cambridge, MA, September 2011

Mroueh, Y., T. Poggio and L. Rosasco, Regularization Predicts While Discovering Taxonomy, MIT-CSAIL-TR-2011-029/CBCL-299, Massachusetts Institute of Technology, Cambridge, MA, June 3, 2011

Poggio, T. and G. Geiger, Werner Reichardt: the man and his scientific legacy, MIT-CSAIL-TR-2011-011, CBCL-297, Massachusetts Institute of Technology, Cambridge, MA, March 4, 2011

Poggio, T., S. Voinea and L. Rosasco, Online Learning, Stability, and Stochastic Gradient Descent, Cornell University Library, arXiv:1105.4701v2 [cs.LG], May 25, 2011

Poggio, T. (sections with J. Mutch, J.Z. Leibo and L. Rosasco), The Computational Magic of the Ventral Stream: Towards a Theory, Nature Precedings, doi:10.1038/npre.2011.6117.1 July 16, 2011

Zhang Y.*, E. Meyers *, N. Bichot, T. Serre, T. Poggio, and R. Desimone, Object decoding with attention in inferior temporal cortex, PNAS Proceedings of the National Academy of Sciences, 108:8850-8855, 2011; Published online before print, May 9, 2011, doi: 10.1073/pnas.1100999108. *These authors contributed equally.

2010:

Bouvrie, J., T. Poggio, R. Lorenzo, S. Smale, and A. Wibisono, Generalization and Properties of the Neural Response, MIT-CSAIL-TR-2010-051/CBCL-292, Massachusetts Institute of Technology, Cambridge, MA, November 19, 2010

Chikkerur, S., T. Serre, C. Tan, and T. Poggio, What and Where: A Bayesian inference theory of visual attention, Vision Research, [doi: 10.1016 /j.visres.2010.05.013], May 20, 2010

De Vito E., S. Pereverzyev, and L. Rosasco, Adaptive Kernel Methods Using the Balancing Principle, Foundations of Computational Mathematics, Volume 10, Number 4, 455-479, [doi: 10.1007/s10208-010-9064-2], August 2010

De Vito, E., L. Rosasco, and A. Toigo, Spectral Regularization for Support Estimation, Advances in Neural Information Processing Systems (NIPS 2010). December 2010.

Jhuang, H., E. Garrote, J. Mutch, X. Yu, V. Khilnani, T. Poggio, A.D. Steele, and T. Serre, Automated home-cage behavioural phenotyping of mice. Nature Communications," 1, Article 68, [doi: 10.1038/ncomms1064], September 7, 2010. Click here for software documentation.

Leibo, J.Z., J. Mutch, S. Ullman, and T. Poggio, From primal templates to invariant recognition, MIT-CSAIL-TR-2010-057/CBCL-293, Massachusetts Institute of Technology, Cambridge, MA, December 4, 2010.

Leibo, J.Z., J. Mutch, L. Rosasco, S. Ullman, and T. Poggio, Learning Generic Invariances in Object Recognition: Translation and Scale, MIT-CSAIL-TR-2010-061/CBCL-294, Massachusetts Institute of Technology, Cambridge, MA, December 30, 2010.

Marr, David, Vision, MIT Press, with a new foreword by Shimon Ullman and afterword by Tomaso Poggio, ISBN-10: 0-262-51462-1; ISBN-13: 978-0-262-51462-0 1982, reissued July, 2010

Meyers, E., Embark, H., Freiwald, W., Serre, T., Kreiman, G., and Poggio T. Examining high level neural representations of cluttered scenes, MIT-CSAIL-TR-2010-034 / CBCL-289, Massachusetts Institute of Technology, Cambridge, MA, July 29, 2010

Mosci, S., A. Villa, A. Verri, and L. Rosasco, A primal-dual algorithm for group sparse regularization with overlapping groups, Advances in Neural Information Processing Systems (NIPS 2010). December 2010.

Mutch, J., U. Knoblich and T. Poggio, CNS: a GPU-based framework for simulating cortically-organized networks. MIT-CSAIL-TR-2010-013 / CBCL-286, Massachusetts Institute of Technology, Cambridge, MA, February 26, 2010

Mutch, J., J.Z. Leibo, S. Smale, L. Rosasco, and T. Poggio, Neurons That Confuse Mirror-Symmetric Object Views, MIT-CSAIL-TR-2010-062/CBCL-295, Massachusetts Institute of Technology, Cambridge, MA, December 31, 2010.

Reddy, L., N. Tsuchyia and T. Serre, "Reading the mind's eye: Decoding object information during mental imagery from fMRI patterns." Neuroimage, 50, pp. 818-825, Feb 2010.doi:10.1167/9.8.782

Rosasco, L., Belkin, M., De Vito, E. On Learning with Integral Operators, Journal of Machine Learning Research, 11, (2010) 905-934 Feb 2010

Roy, J.E., Riesenhuber, M., T. Poggio and E.K. Miller, "Prefrontal cortex activity during flexible categorization". Journal of Neuroscience, 30:8519-8528, 2010

Serre, T. and T. Poggio “A Neuromorphic Approach to Computer Vision”, Communications of the ACM (online), Vol . 53, No. 10, October 2010 [doi :10.1145/1831407.1831425]

Smale, S., L. Rosasco, J. Bouvrie, A. Caponnetto, and T. Poggio, "Mathematics of the Neural Response", Foundations of Computational Mathematics, Vol. 10, 1, 67-91, June 2009 (online); February 2010 (print)

Wibisono, A., J. Bouvrie, L. Rosasco, and T. Poggio, "Learning and Invariance in a Family of Hierarchical Kernels", MIT-CSAIL-TR-2010-035 / CBCL-290, Massachusetts Institute of Technology, Cambridge, MA, July 30, 2010

2009:

Bileschi, S.,"Fully Automatic Calibration of LIDAR and Video Streams From a Vehicle" 3-D Digital Imaging and Modeling (3DIM ICCV Workshop), 2009

Bouvrie, J., L. Rosasco, G. Shakhnarovich, and S. Smale, "Notes on the Shannon Entropy of the Neural Response", CBCL-281, MIT-CSAIL-TR-2009-049, Massachusetts Institute of Technology, Cambridge, MA, October 9, 2009

Bouvrie, J. , L. Rosasco, and T. Poggio. "On Invariance in Hierarchical Models". Advances in Neural Information Processing Systems (NIPS) 22, 2009.

Cao, R., B.T. Higashikubo, J.A. Cardin, U. Knoblich, R. Ramos, M.T. Nelson, C.I. Moore and J.C. Brumberg. "Pinacidil induces vascular dilation and hyperemia in vivo and does not impact biophysical properties of neurons and astrocytes in vitro." Cleve. Clin. J. Med. 76, 2009 [doi: 10.3949/ccjm.76.s2.16]

Cardin, J.A., M. Carlén, K. Meletis, U. Knoblich, F. Zhang, K. Deisseroth, L.H. Tsai and C.I. Moore. "Driving fast-spiking cells induces gamma rhythm and controls sensory responses." Nature 459(7247):663-667, 2009 [doi: 10.1038/nature08002]

Chikkerur, S., T. Serre, and T. Poggio, "A Bayesian inference theory of attention: neuroscience and algorithms" MIT-CSAIL-TR-2009-047/CBCL-280, Massachusetts Institute of Technology, Cambridge, MA, October 3, 2009.

Chikkerur, S., T. Serre, and T. Poggio, "Attentive processing improves object recognition" MIT-CSAIL-TR-2009-046 /CBCL-279, Massachusetts Institute of Technology, Cambridge, MA, October 2, 2009.

Chikkerur, S., C. Tan, T. Serre, and T. Poggio, "An integrated model of visual attention using shape-based features" MIT-CSAIL-TR-2009-029 / CBCL-278, Massachusetts Institute of Technology, Cambridge, MA, June 20, 2009.

De Mol, C., E. De Vito and L. Rosasco. "Elastic-Net Regularization in Learning Theory", to be published in the Journal of Complexity, available online January 30, 2009.

Ostrovsky, Y., Meyers, E., Ganesh, S., Mathur, U., Sinha P. " Visual Parsing After Recovery From Blindness." Psychological Science, 20:1467-1491, 2009

Rosasco, L., S. Mosci, M. Santoro, A. Verri, and S. Villa, "Iterative Projection Methods for Structured Sparsity Regularization", MIT-CSAIL-TR-2009-50 / CBCL-282, Massachusetts Institute of Technology, Cambridge, MA, October 14, 2009.

Terashima, Y. "Scene Classification with a Biologically Inspired Method", CBCL paper #277/CSAIL Technical Report#2009-020, CBCL-277 Massachusetts Institute of Technology, Cambridge, MA, May 10, 2009.

Wibisono, A., L. Rosasco, T. Poggio, "Sufficient Conditions for Uniform Stability of Regularization Algorithms", CBCL paper #284/CSAIL Technical Report#MIT-CSAIL-TR-2009-060, Massachusetts Institute of Technology, Cambridge, MA, December 1, 2009.

Yokono, J.J., and T.Poggio. "Object Recognition Using Boosted Oriented Filter Based Local Descriptors." IEEJ Transactions on Electronics, Information and Systems 129 5 (2009): 806-11+5, 2009.

Yokoyama, M., and T. Poggio. "A Contour-Based Moving Object Detection." IEEJ Transactions on Electronics, Information and Systems 129 5 (2009): 812-17+6, 2009.

Yu, X., A. Steele, V. Khilnani, E. Garrote, H. Jhuang, T. Serre, and T. Poggio, "Automated home-cage behavioral phenotyping of mice,MIT-CSAIL-TR-2009-052 CBCL-283, Massachusetts Institute of Technology, Cambridge, MA, October 26, 2009.

2008:

Barla, A., Mosci, S., Rosasco, L. and Verri, A. "A method for robust variable selection with significance assessments" 16th European Symposium on Artificial Neural Networks.

Bileschi, S.M. Object Detection at Multiple Scales Improves Accuracy, ICPR 2008.

Bileschi, S.M. A Multi-Scale Generalization of the HoG and HMAX Image Descriptors for Object Detection, CBCL paper #271/CSAIL Technical Report #2008-019, Massachusetts Institute of Technology, Cambridge, MA, April 9, 2008.

Bouvrie, J., T. Ezzat, and T. Poggio. "Localized Spectro-Temporal Cepstral Analysis of Speech", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Las Vegas, 2008.

Caponnetto, A., T. Poggio and S. Smale On a model of visual cortex: learning invariance and selectivity from image sequences, CBCL paper#272/CSAIL Technical Report #2008-030 , Massachusetts Institute of Technology, Cambridge, MA, April 4, 2008

De Mol, C., E. De Vito and L. Rosasco. "Elastic-Net Regularization in Learning Theory", CBCL paper #273/ CSAIL Technical Report #TR-2008-046 , Massachusetts Institute of Technology, Cambridge, MA, July 24, 2008.

De Vito, E., S. Pereverzyev, and L. Rosasco. "Adaptive Kernel Methods Using the Balancing Principle", CBCL paper #275/CSAIL Technical Report#TR-2008-062Massachusetts Institute of Technology, Cambridge, MA, October 16, 2008.

Ezzat, T. and T. Poggio. "Discriminative Word-Spotting Using Ordered Spectro-Temporal Patch Features", SAPA Workshop, Interspeech, Brisbane, Australia, 2008

Geiger, G., C. Cattaneo, R. Galli, U. Pozzoli, M. Lorusso, A. Facoetti, and M. Molteni. "Wide and diffuse perceptual modes characterize dyslexics in vision and audition", Perception Vol. 37, Issue 11, Pages 1745 – 1764, November 17, 2008.

Kouh, M. and T. Poggio. “A Canonical Neural Circuit for Cortical Nonlinear Operations” Neural ComputationVol. 20, No. 6, Pages 1427-1451, June 2008.

LeCun, Y., D.G. Lowe, J. Malik, J. Mutch, P. Perona, and T. Poggio. Object Recognition, Computer Vision, and the Caltech 101: A Response to Pinto et al., PLoS Computational Biology, Posted Online March 2008.

Lo Gerfo L., Rosasco L., Odone F., De Vito E. and Verri, A. "Spectral Algorithms for Supervised Learning", Neural Computation. 20: 1873-1897, 2008.

Meyers, E., and L. Wolf. Using Biologically Inspired Visual Features for Face Processing.  International Journal of Computer Vision, Vol 76, No. 1, 93-104, 2008.

Meyers, E.M., D. J. Freedman, G. Kreiman, E.K. Miller, and T. Poggio. "Dynamic Population Coding of Category Information in Inferior Temporal and Prefrontal Cortex".  Journal of Neurophysiology Vol. 100: 1407-1419, June 18, 2008.

Lo Gerfo L., Rosasco L., Odone F., De Vito E. and Verri, A. "Spectral Algorithms for Supervised Learning", Neural Computation, 20: 1873-1897, 2008

Mosci, S.; A. Barla; A. Verri and L. Rosasco. " Finding Structured Gene Signatures". Proc. of IEEE BIBM, Philadelphia, PA. USA, 2008.

Rosasco, L., M. Belkin, and E. De Vito. "A Note on Perturbation Results for Learning Empirical Operators ", CBCL paper #274/ CSAIL Technical Report #TR-2008-052 , Massachusetts Institute of Technology, Cambridge, MA, August 19, 2008.

S. Smale, L. Rosasco, J. Bouvrie, A. Caponnetto, and T. Poggio. "Mathematics of the Neural Response", CBCL Paper #276/MIT CSAIL Technical Report #TR2008-070, Massachusetts Institute of Technology, Cambridge, MA, November, 2008

2007:

Bileschi, S. Wolf, L. "Image representations beyond histograms of gradients: The role of Gestalt descriptors", Proc. of IEEE Conference on Computer Vision and Pattern Recognition, 2007 - CVPR '07, June 2007, Pages 1-8, Digital Object Identifier 10.1109/CVPR.2007.383122

Bouvrie, J. and P. Sinha. Visual object concept discovery: Observations in congenitally blind children, and a computational approach, Neurocomputing, Volume 70, Issues 13-15, pp.2218-2233, 2007.

Cadieu, C., M. Kouh, A. Pasupathy, C. Connor, M. Riesenhuber, and T. Poggio. A Model of V4 Shape Selectivity and Invariance, Journal of Neurophysiology, Vol. 98, 1733-1750, June, 2007.

Ezzat, T., J. Bouvrie, and T. Poggio. Spectro-Temporal Analysis of Speech Using 2-D Gabor Filters, Interspeech, Belgium 2007.

Ezzat, T., J. Bouvrie, and T. Poggio. AM-FM Demodulation of Spectrograms using 2-D Max-Gabor Analysis, ICASSP, Hawaii, 2007.

Heisele, B., T. Serre and T. Poggio. A Component-based Framework for Face Detection and Identification, International Journal of Computer Vision, 74(2), pp. 167-181, 2007.

Jhuang H., T. Serre, L. Wolf and T. Poggio. A Biologically Inspired System for Action Recognition, In: Proceedings of the Eleventh IEEE International Conference on Computer Vision (ICCV), 2007.

Knoblich, U., J. Bouvrie and T. Poggio. Biophysical Models of Neural Computation: Max and Tuning Circuits, CBCL paper, April 20, 2007.

Masquelier, T., T. Serre, S. Thorpe and T. Poggio. Learning complex cell invariance from natural videos: A plausibility proof, CBCL Paper #269/AI Technical Report #2007-060, Massachusetts Institute of Technology, Cambridge, MA, December, 2007.

Poggio, T. “Neuroscience: New Insights for AI?”.  In: Web Intelligence Meets Brain Informatics, First WICI International Workshop, WImBI 2006,Beijing, China, December 2006.

Poggio, T. "Memories of a friend of Odile" in Odile Crick: A Memorial Exhibition, curator Becky Cohen, The Salk Institute, 2004.

Poggio. T. How the Brain Might Work: The Role of Information and Learning in Understanding and Replicating Intelligence. In: Information: Science and Technology for the New Century, Editors: G. Jacovitt, A. Pettorossi, R. Consolo and V. Senni, Lateran University Press, Quaderni Sefir, 7, pp. 45-61, 2007.

Rifkin, R., K. Schutte, D. Saad, J. Bouvrie, and J. Glass. Noise Robust Phonetic Classification with Linear Regularized Least Squares and Second-Order Features, ICASSP, Honolulu, 2007.

Rifkin, R.,. and R.A. Lippert. Notes on Regularized Least-Squares, CBCL Paper #268/AI Technical Report #2007-019, Massachusetts Institute of Technology, Cambridge, MA, May, 2007.

Rifkin, R., J. Bouvrie, K. Schutte, S. Chikkerur, M. Kouh, T. Ezzat and T. Poggio. Phonetic Classification Using Hierarchical, Feed-forward, Spectro-temporal Patch-based Architectures, CBCL Paper #267/AI Technical Report #2007-019, Massachusetts Institute of Technology, Cambridge, MA, March, 2007.

Serre, T., A. Oliva and T. Poggio. A Feedforward Architecture Accounts for Rapid Categorization, Proceedings of the National Academy of Sciences (PNAS), Vol. 104, No. 15, 6424-6429, 2007.

Serre, T., G. Kreiman, M. Kouh, C. Cadieu, U. Knoblich and T. Poggio, A quantitative theory of immediate visual recognition. Progress in Brain ResearchVol. 165, 33-56, 2007.

Serre, T., L. Wolf, S. Bileschi, M. Riesenhuber and T. Poggio. Robust Object Recognition with Cortex-like Mechanisms, IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 3, 411-426, 2007.

Smale, S., T. Poggio, A. Caponnetto, and J. Bouvrie. Derived Distance: towards a mathematical theory of visual cortex, CBCL Paper, Massachusetts Institute of Technology, Cambridge, MA, November, 2007.

Wolf, L., H.Jhuang and T.Hazan. Modeling Appearances with Low-Rank SVM, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007.

Zoccolan, D., M. Kouh, T. Poggio, and James J. DiCarlo . Trade-off between object selectivity and tolerance in monkey inferotemporal cortex, Journal of Neuroscience, Volume 27(45), pp.12292–12307, November, 2007.

2006:

Bileschi, Stanley (Ph.D. Thesis, EECS, MIT, May 2006): StreetScenes: Towards Scene Understanding in Still Images.

Bileschi, S. and L. Wolf. A Unified System for Object Detection, Texture Recognition and Context Analysis Based on the Standard Model Feature Set. In: British Machine Vision Conference (BMVC), 2006.

Bouvrie, J. and T. Ezzat. An Incremental Algorithm for Signal Reconstruction from Short-time Fourier Transform Magnitude. In: Ninth International Conference on Spoken Language Processing (ICSLP-Pittsburgh, PA), 2006.

Caponnetto, A. and A. Rakhlin. Stability Properties of Empirical Risk Minimization over Donsker Classes, Journal of Machine Learning Research, Vol. 7, 2565-2583, 2006.

Caponnetto, A. and Y. Yao. Adaptation for Regularization Operators in Learning Theory, CBCL Paper #265/AI Technical Report #063, Massachusetts Institute of Technology, Cambridge, MA, September, 2006.

Caponnetto, A. Optimal Rates for Regularization Operators in Learning Theory, CBCL Paper #264/AI Technical Report #062, Massachusetts Institute of Technology, Cambridge, MA, September, 2006.

Chikkerur, S. and L. Wolf. Empirical Comparison between Hierarchical Fragments Based and Standard Model Based Object Recognition Systems, CBCL Paper #MMVI-0I, Massachusetts Institute of Technology, Cambridge, MA, March, 2006.

Das, Sanmay (Ph.D. Thesis, EECS, MIT, April 2006): Dealers, Insiders and Bandits: Learning and Its Effects on Market Outcomes.

Ezzat, T., J. Bouvrie and T. Poggio. Max-Gabor Analysis and Synthesis of Spectrograms. In: Ninth International Conference on Spoken Language Processing (ICSLP-Pittsburgh, PA), 2006.

Freedman, D.J., Riesenhuber, M., Poggio, T., and Miller, E.K. Experience dependent sharpening of visual shape selectivity in inferior temporal cortex, Cerebral Cortex, 16: 1631-1644, 2006.

Knoblich, U., J. Bouvrie, and T. Poggio. Biophysical Models of Neural Computation: Max and Tuning Circuits, In: Web Intelligence Meets Brain Informatics, First WICI International Workshop (WImBI 2006) Bejing, China, December 2006.

Kreiman, G., C.P. Hung, A. Kraskov, R.Q. Quiroga, T. Poggio and J.J. DiCarlo. Object Selectivity of Local Field Potentials and Spikes in the Macaque Inferior Temporal Cortex, Neuron, Vol. 49, 433-445, 2006.

Lorusso, M.L., A. Facoetti, C. Cattaneo, S. Presenti, R. Galli, M. Molteni, and G. Geiger. Training visual-spatial attention in developmental dyslexia. In: Dyslexia in Children: New Research, Hayes, B. (ed), Nova Science Publishers, 143-160. (2006).

Mukherjee, S., P. Niyogi, T. Poggio and R. Rifkin. Learning Theory: Stability is Sufficient for Generalization and Necessary and Sufficient for Consistency of Empirical Risk Minimization, Advances in Computational Mathematics, 25, 161-193, 2006.

Poggio, T. Neuroscience: New Insights for AI? , In: Web Intelligence Meets Brain Informatics, First WICI International Workshop (WImBI 2006) Bejing, China, December 2006.

Rakhlin, Alexander (Ph.D. Thesis, BCS, MIT, April 2006): Applications of Empirical Processes in Learning Theory: Algorithmic Stability and Generalization Bounds.

Rakhlin, A. and A. Caponnetto. Stability of K-means Clustering. In: Neural Information Processing Systems Conference, 2006.

Serre, Thomas R. (Ph.D. Thesis, BCS, MIT, March 2006): Learning a Dictionary of Shape-Components in Visual Cortex: Comparison with Neurons, Humans and Machines.

Serre, T. Learning a Dictionary of Shape-Components in Visual Cortex: Comparison with Neurons, Humans and Machines, CBCL Paper #260/AI Technical Report #028, Massachusetts Institute of Technology, Cambridge, MA, March, 2006.

Soni, Neha (S.M. Thesis, EECS, MIT, February 2006): Sequence Motifs Predictive of Tissue-specific Skipping.

Tropea, D., G. Kreiman, A. Lyckman, S. Mukherjee, H. Yu, S. Horng and M. Sur. Distinct Gene Systems Mediating Activity-dependent Plasticity in Visual Cortex, Nature Neuroscience, 9, 660-668, 2006.

Wolf, L. and S. Bileschi. A Critical View of Context. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2006.

Wolf, L., S. Bileschi and E. Meyers. Perception Strategies in Hierarchical Vision Systems. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2006.

Wolf F., T. Poggio, P. Sinah Human Document Classification Using Bags of Words , CBCL paper #263/CSAIL Technical Report #2006-054, Massachusetts Institute of Technology, Cambridge, MA, August 9, 2006.

Yokono, J.J. and T. Poggio. A Multiview Face Identification Model With No Geometric Constraints, Sony Intelligence Dynamics Laboratories, Inc. March, 2006.

2005:

Balas, B. Using Computational Models to Study Texture Representations in the Human Visual System, CBCL Paper #244/AI Memo #2005-002, Massachusetts Institute of Technology, Cambridge, MA, February, 2005.

Cadieu, Charles F. (S.M. Thesis, EECS, MIT, May 2005): Modeling Shape Representation in Visual Cortex Area V4.

Caponnetto, A. A Note on the Role of Squared Loss in Regression, CBCL Paper, Massachusetts Institute of Technology, Cambridge, MA, June 2005.

Caponnetto, A. and E. de Vito. Fast Rates for Regularized Least-squares Algorithm, CBCL Paper #248/AI Memo #2005-013, Massachusetts Institute of Technology, Cambridge, MA, April, 2005.

Caponnetto, A. and A. Rakhlin. Some Properties of Empirical Risk Minimization over Donsker Classes, CBCL Paper #250/AI Memo #2005-018, Massachusetts Institute of Technology, Cambridge, MA, May 2005.

Caponnetto, A., L. Rosasco, E. de Vito and A. Verri. Empirical Effective Dimension and Optimal Rates for Regularized Least Squares Algorithm, CBCL Paper #252/AI Memo #2005-019, Massachusetts Institute of Technology, Cambridge, MA, May 2005.

Das, S. Learning to Trade with Insider Information, CBCL Paper #255/AI Memo #2005-028, Massachusetts Institute of Technology, Cambridge, MA, October, 2005.

Das, S. "A Learning Market-Maker in the Glosten-Milgrom Model", Quantitative Finance, Vol. 5, No. 2, 169-180, April 2005.

Das, S. and E. Kamenica. Two-Sided Bandits and the Dating Market. In: Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, UK, 947-952, August 2005.

de Vito, E. and A. Caponnetto. Risk Bounds for Regularized Least-squares Algorithm with Operator-valued Kernels, CBCL Paper #249/AI Memo #2005-015, Massachusetts Institute of Technology, Cambridge, MA, May, 2005.

Ezzat, T., E. Meyers, J. Glass and T. Poggio. Morphing Spectral Envelopes Using Audio Flow. In: Proceedings of Interspeech-Eurospeech Conference, Lisbon, Portugal, 2545-2548, September 2005.

Freedman, D.J., M. Riesenhuber, T. Poggio and E.K. Miller. Experience-Dependent Sharpening of Visual Shape Selectivity in Inferior Temporal Cortex, Cerebral Cortex, December 2005.

Geiger, G. and D. Amara. Towards the Prevention of Dyslexia, CBCL Paper #256/AI Memo #2005-029, Massachusetts Institute of Technology, Cambridge, MA, October 2005.

Han, K., G. Yeo, P. An, C.B. Burge and P.J. Grabowski. A Combinatorial Code for Splicing Silencing: UAGG and GGGG Motifs, PLoS Biology, Vol. 3, Issue 5, e158, 0001-0018, May 2005.

Hung, C., G. Kreiman, T. Poggio and J. DiCarlo. Ultra-fast Object Recognition from Few Spikes, CBCL Paper #253, Massachusetts Institute of Technology, Cambridge, MA, July 2005.

Hung, C.P., G. Kreiman, T. Poggio and J.J. DiCarlo. Fast Readout of Object Identity from Macaque Inferior Temporal Cortex, Science, Vol. 310, 863-866, 2005.

Ivanov, Y., T. Serre and J. Bouvrie. Error Weighted Classifier Combination for Multi-modal Human Identification, CBCL Paper #258/AI Memo #2005-035, Massachusetts Institute of Technology, Cambridge, MA, December, 2005.

Kreiman, G., I. Fried and C. Koch. Responses of Single Neurons in the Human Brain during Flash Suppression. In: Binocular Rivalry and Perceptual Ambiguity, (Eds.) R. Blake and D. Alais, MIT Press, Cambridge, MA, Chapter 12, 213-230, 2005.

Lippert, J.R. and R. Rifkin. Asymptotics of Gaussian Regularized Least-Squares, CBCL Paper #257/AI Memo #2005-030, Massachusetts Institute of Technology, Cambridge, MA, October 2005.

Martin, Ian S. (S.M. Thesis, EECS, MIT, May 2005): Robust Learning and Segmentation for Scene Understanding.

Quiroga, R.Q., L. Reddy, G. Kreiman, C. Koch and I. Fried. Invariant Visual Representation by Single Neurons in the Human Brain, Nature-Letters, Vol. 435, 1102-1107, June 2005.

Rakhlin, A., S. Mukherjee and T. Poggio. Stability Results in Learning Theory, Analysis and Applications, Vol. 3, No. 4, 397-417, 2005.

Rakhlin, A., D. Panchenko and S. Mukherjee. Risk Bounds for Mixture Density Estimation, ESAIM: Probability and Statistics, Vol. 9, 220-229, June 2005.

Serre, T., M. Kouh, C. Cadieu, U. Knoblich, G. Kreiman and T. Poggio. A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual Cortex, CBCL Paper #259/AI Memo #2005-036, Massachusetts Institute of Technology, Cambridge, MA, October, 2005.

Serre, T., L. Wolf and T. Poggio. Object Recognition with Features Inspired by Visual Cortex. In: Proceedings of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society Press, San Diego, June 2005.

Sigala, R., T. Serre, T. Poggio and M. Giese. Learning Features of Intermediate Complexity for the Recognition of Biological Motion. In: ICANN 2005, Warsaw, Poland, 241-246, September 2005.

Skelley, James P. (S.M. Thesis, EECS, MIT, August 2005): Experiments in Expression Recognition.

Sweet-Cordero, A., S. Mukherjee, A. Subramanian, H. You, J.J. Roix, C. Ladd-Acosta, J. Mesirov, T.R. Golub and T. Jacks. An Oncogenic KRAS2 Expression Signature Identified by Cross-species Gene-expression Analysis, Nature Genetics, 37, 1, 48-55, 2005.

Wolf, L. and S. Bileschi. Combining Variable Selection with Dimensionality Reduction, CBCL Paper #247/AI Memo #2005-009, Massachusetts Institute of Technology, Cambridge, MA, March 2005.

Wolf, L. and I. Martin. Robust Boosting for Learning from Few Examples. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005.

Wolf, L. and A. Shashua. Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-based Approach, Journal of Machine Learning Research, 6, 1855-1887, 2005.

Wu, Jia Jane (S.M. Thesis, EECS, MIT, May 2005): Comparing Visual Features for Morphing Based Recognition.

Yeo, G., E. Van Nostrand, D. Holste, T. Poggio and C.B. Burge. Identification and Analysis of Alternative Splicing Events Conserved in Human and Mouse, Proceedings of the National Academy of Sciences (PNAS), 102, 8, 2850-2855, 2005.

Yokono, J.J. and T. Poggio. Boosting a Biologically Inspired Local Descriptor for Geometry-free Face and Full Multi-view 3D Object Recognition, CBCL Paper #254/AI Memo #2005-023, Massachusetts Institute of Technology, Cambridge, MA, July 2005.

Yokoyama, M. and T. Poggio. A Contour-Based Moving Object Detection and Tracking. In: Proceedings of Second Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (in conjunction with ICCV 2005), Beijing, China, October 15-16, 2005.

Zoccolan, D., D.D. Cox and J.J. DiCarlo. Multiple Object Response Normalization in Monkey Infero-temporal Cortex, Journal of Neuroscience, 25(36), 8150-64, 2005.

2004:

Bouvrie, Jacob V. (S.M. Thesis, EECS, MIT, June 2004): Multi-Source Contingency Clustering.

Cadieu, C., M. Kouh, M. Riesenhuber and T. Poggio. Shape Representation in V4: Investigating Position-specific Tuning for Foundary Conformation with the Standard Model of Object Recognition, CBCL Paper #241/AI Memo #2004-024, Massachusetts Institute of Technology, Cambridge, MA, November, 2004.

Cox, D., E. Meyers and P. Sinha. Contextually Evoked Object-specific Responses in Human Visual Cortex, Science, Vol. 303, No. 5667, 115-117, 2004.

Crick, F., C. Koch, G. Kreiman and I. Fried. Consciousness and Neurosurgery, Neurosurgery, 55, 272-282, 2004.

Ezzat, T., G. Geiger and T. Poggio. Trainable Videoreaslistic Speech Animation. In: Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition (FGR2004, Seoul, Korea), 57-64, 2004.

Fischer, Robert (S.M. Thesis, Math & Natural Sciences, MIT/Univ. of Applied Science Darmstadt, Germany, October 2004): Automatic Facial Expression Analysis and Emotional Classification.

Heisele, B. and T. Koshizen. Components for Face Recognition. In: Proceedings of the 6th International Conference on Automatic Face and Gesture Recognition, Seoul, Korea, 153-158, 2004.

Ivanov, I., B. Heisele and T. Serre. Using Component Features for Face Recognition. In: Proceedings of the 6th International Conference on Automatic Face and Gesture Recognition, Seoul, Korea, 421-426, 2004.

Kouh, M. and T. Poggio. A General Mechanisms for Tuning: Gain Control Circuits and Synapses Underlie Tuning of Cortical Neurons, CBCL Paper #245/AI Memo #2004-031, Massachusetts Institute of Technology, Cambridge, MA, December 2004.

Kreiman, G. Neural Coding: Computational and Biophysical Perspectives, Physics of Life Reviews, 2, 71-102, 2004.

Kreiman, G. Identification of Sparsely Distributed Clusters of Cis-Regulatory Elements in Sets of Co-expressed Genes, Nucleic Acids Research, 32, 2889-2900, 2004.

Kreiman, G., I. Fried and C. Koch. Responses of Single Neurons in the Human Brain during Flash Suppression. In: Binocular Rivalry and Perceptual Ambiguity, (Eds.) R. Blake and D. Alais, MIT Press, Cambridge, MA, Chapter 12, 2005, to appear.

Kreiman, G., C. Hung, T. Poggio and J. DiCarlo. Selectivity of Local Field Potentials in Macaque Inferior Temporal Cortex, CBCL Paper #240/AI Memo #2004-020, Massachusetts Institute of Technology, Cambridge, MA, September, 2004.

Kyriakides, Alexandros (S.M. Thesis, EECS, MIT, February 2004): Supervised Information Retrieval for Text and Images.

Lampl, I., D. Ferster, T. Poggio and M. Riesenhuber. Intracellular Measurements of Spatial Integration and the MAX Operation in Complex Cells of the Cat Primary Visual Cortex, Journal of Neurophysiology, 92, 2704-2713, 2004.

Leung, Brian (S.M. Thesis, EECS, MIT, May 2004): Component-based Car Detection in Street Scene Images.

Lorusso, M.L., A. Facoetti, S. Pesenti, C. Cattaneo, M. Molteni and G. Geiger. Wider Recognition in Peripheral Vision Common to Different Subtypes of Dyslexia, Vision Research, 44, 2413-2424, 2004.

Paysan, Pascal (S.M. Thesis, Computer Science, Fachochschule Esslingen, February 2004): Stereovision-based Vehicle Classification Using Support Vector Machines.

Poggio, T. "Francis H. C. Crick: Memories of a friend of Francis and Odile", in the Crick Memorial Book: A Memorial Exhibition, curator Becky Cohen, The Salk Institute, 2004.

Poggio, T. Q & A - Discussion, Current Biology, Vol. 14, Issue 23, R985-R986, December 2004.

Poggio, T. "La Teoria del 'Learning': Introduzione e Applicazioni". In: La Matematica nel Mondo della Natura, (Eds.) C. Bartocci, G.I. Bischi, L.C. Orsini, E. Carletti, G. Manuzio, R. Parodi, F. Pastrone, T. Poggio, Erga Edizioni, Genova, 131-138, 2004.

Poggio, T. and E. Bizzi. Generalization in Vision and Motor Control, Nature, Vol. 431, 768-774, 2004.

Poggio, T.P. and M. Poggio. Francis Harry Compton Crick, Physics Today, 80-81, November 2004.

Poggio, T., R. Rifkin, S. Mukherjee and P. Niyogi. General Conditions for Predictivity in Learning Theory, Nature, Vol. 428, 419-422, 2004.

Rakhlin, A., S. Mukherjee, and T. Poggio. On Stability and Concentration of Measure, CBCL Paper, Massachusetts Institute of Technology, Cambridge, MA, June 2004.

Rakhlin, A., D. Panchencko and S. Mukherjee. Risk Bounds for Mixture Density Estimation, CBCL Paper #233/AI Memo #2004-001, Massachusetts Institute of Technology, Cambridge, MA, January, 2004.

Riesenhuber, M., I. Jarudi, S. Gilad and P. Sinha. Face Processing in Humans is Compatible with A Simple Shape-based Model of Vision, Proc. R. Soc. Lond. B (Suppl.), DOI 10.1098/rsbl.2004.0216, 04BL0061.S1-04BL0061.S3, 2004.

Riesenhuber, M., I. Jarudi, S. Gilad and P. Sinha Face Processing in Humans is Compatible with a Simple-Shape-based Model of Vision, CBCL Paper #236/AI Memo #2004-006, Massachusetts Institute of Technology, Cambridge, MA, March, 2004.

Rifkin, R. and A. Klautau. In Defense of One-vs-All Classification, Journal of Machine Learning Research, Vol. 5, 101-141, 2004.

Sadr, J. and P. Sinha. "Object Recognition and Random Image Structure Evolution," Cognitive Science, Vol. 28, 259-287, 2004.

Schneider, R. and M. Riesenhuber. On the Difficulty of Feature-based Attentional Modulations in Visual Object Recognition: A Modeling Study, CBCL Paper #235/AI Memo #2004-004, Massachusetts Institute of Technology, Cambridge, MA, February, 2004.

Serre, T. and M. Riesenhuber. Realistic Modeling of Simple and Complex Cell Tuning in the HMAX Model, and Implications for Invariant Object Recognition in Cortex, CBCL Paper #239/AI Memo #2004-017, Massachusetts Institute of Technology, Cambridge, MA, August, 2004.

Serre, T., L. Wolf and T. Poggio. A New Biologically Motivated Framework for Robust Object Recognition, CBCL Paper #243/AI Memo #2004-026, Massachusetts Institute of Technology, Cambridge, MA, November, 2004.

Shimizu, H. and T. Poggio. Direction Estimation of Pedestrian from Multiple Still Images. In: IEEE Intelligent Vehicles Symposium 2004, Parma, Italy, June 14-17, 2004.

Su, A.I., T. Wiltshire, S. Batalov, H. Lapp, K.A. Ching, D. Block, J. Zhang, R. Soden, M. Hayakawa, G. Kreiman, M.P. Cooke, J.R. Walker and J.B. Hogenesc. A Gene Atlas of the Mouse and Human Protein-Encoding Transcriptomes, Proceedings of the National Academy of Sciences, USA 101, 6062-6067, 2004.

Wang, Z., M.E. Rolish, G. Yeo, V. Tung, M. Mawson and C.B. Burge. Systematic Identification and Analysis of Exonic Splicing Silencers, Cell, 119, 831-845, 2004.

Weyrauch, B., J. Huang, B. Heisele and V. Blanz. Face Processing in Video. In: Proceedings of 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2004), IEEE Computer Society Press, Washington, DC, 2004, in press.

Wolf, L. and I. Martin. Regularization through Feature Knock Out, CBCL Paper #242/AI Memo #2004-025, Massachusetts Institute of Technology, Cambridge, MA, November, 2004.

Wolf, L., A. Shashua and S. Mukherjee. Selecting Relevant Genes with a Spectral Approach, CBCL Paper #234/AI Memo #2004-002, Massachusetts Institute of Technology, Cambridge, MA, January, 2004.

Yeo, G., D. Holste, G. Kreiman and C. Burge. Variation in Alternative Splicing across Human Tissues, Genome Biology, 5, R74, 2004.

Yeo, Gene W. (Ph.D. Thesis, EECS, MIT, November 2004): Identification, Improved Modeling and Integration of Signals to Predict Constitutive and Alternative Splicing.

Yeo, G., S. Hoon, B. Venkatesh and C. Burge. Variation in Sequence and Organization of Splicing Regulatory Elements in Vertebrate Genes, Proceedings of the National Academy of Sciences (PNAS), 191(44), 15700-15705, 2004.

Yokono, J.J. and T. Poggio. Oriented Filters for Object Recognition: An Empirical Study. In: Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition (FGR2004, Seoul, Korea), 755-760, 2004.

Yokono, J.J. and T. Poggio. Rotation Invariant Object Recognition from One Training Example, CBCL Paper #238/AI Memo #2004-010, Massachusetts Institute of Technology, Cambridge, MA, April, 2004.

Yokono, J.J. and T. Poggio. Evaluation of Sets of Oriented and Non-oriented Receptive Fields as Local Descriptors, CBCL Paper #237/AI Memo #2004-007, Massachusetts Institute of Technology, Cambridge, MA, March, 2004.

2003:

Balas, B.J. and P. Sinha. Dissociated Dipoles: Image Representation Via Non-localComparisons, CBCL Paper #229/AI Memo #2003-018, Massachusetts Institute of Technology, Cambridge, MA, August 2003.

Bileschi, S.M. (S.M. Thesis, EECS, MIT, January 2003): Advances in Component-based Face Detection.

Bileschi, S.M. and B. Heisele. Advances in Component Based Face Detection. In: Proceedings of the 2003 IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG 2003, Nice France), 149-156, 2003.

Blanz, V., C. Basso, T. Poggio and T. Vetter. Reanimating Faces in Images and Video. In: Proceedings of Eurographics, (Eds. P. Brunet and D. Fellner), Granada, Spain, Vol. 22, No. 3, 2003.

Das, S. Intelligent Market-Making in Artificial Financial Markets, CBCL Paper #226/AI Technical Report #2003-005, Massachusetts Institute of Technology, Cambridge, MA, May 2003.

Das, Sanmay (S.M. Thesis, EECS, MIT, June 2003): Intelligent Market-Making in Artificial Markets.

Dror, R.O., J.G. Murnick, N.A. Rinaldi, V.D. Marinescu, R.M. Rifkin and R.A. Young. Bayesian Approach to Transcript Estimation from Gene Array Data: The BEAM Technique. In: Proceedings of the Sixth Annual International Conference on Research in Computational Molecular Biology, Washington, D.C., April 2002, in press.

Freedman, D.J., M. Riesenhuber, T. Poggio, and E.K. Miller. Comparison of Primate Prefrontal and Inferior Temporal Cortices during Visual Categorization, Journal of Neuroscience, 23, 5235-5246, 2003.

Geiger, G., T. Ezzat and T. Poggio. Perceptual Evaluation of Video-realistic Speech, CBCL Paper #224/AI Memo #2003-003, Massachusetts Institute of Technology, Cambridge, MA, February 2003.

Giese, M. and T. Poggio. Neural Mechanisms for the Recognition of Biological Movements, Nature Neuroscience Review, Vol. 4, 179-192, March 2003.

Heisele, B. Visual Object Recognition with Supervised Learning, IEEE Intelligent Systems - AI's Second Century, 38-42, May-June 2003.

Heisele, B., P. Ho, J. Wu and T. Poggio. Face Recognition: Component-based versus Global Approaches, Computer Vision and Image Understanding, Vol. 91, No. 1/2, 6-21, 2003.

Heisele, B., T. Serre, S. Prentice and T. Poggio. Hierarchical Classification and Feature Reduction for Fast Face Detection with Support Vector, Pattern Recognition, 36, 2007-2017, 2003.

Huang, J. (S.M. Thesis, EECS, MIT, January 2003): Component-based Face Recognition with 3D Morphable Models.

Jarudi, I.N. and P. Sinha. Relative Contributions of Internal and External Features to Face Recognition, CBCL Paper #225/AI Memo #2003-004, Massachusetts Institute of Technology, Cambridge, MA, March 2003.

Kim, Brian (S.M. Thesis, EECS, MIT, June 2003): Multi-Source Human Identification.

Kouh, M. and M. Riesenhuber. Investigating Shape Representation in Area V4 with HMAX: Orientation and Grating Selectivities, CBCL Paper #231/AIM #2003-021, Massachusetts Institute of Technology, Cambridge, MA, September 2003.

Louie, J. A Biological Model of Object Recognition with Feature Learning, CBCL Paper #227/AI Technical Report #2003-009, Massachusetts Institute of Technology, Cambridge, MA, May 2003.

Louie, Jennifer (S.M. Thesis, EECS, MIT, May 2003): A Biological Model of Object Recognition with Feature Learning.

Morgenstern, C. and B. Heisele. Component-based Recognition of Objects in an Office Environment, CBCL Paper #232/AI Memo #2003-024, Massachusetts Institute of Technology, Cambridge, MA, November 2003.

Mukherjee, S. Classifying Microarray Data Using Support Vector Machines. In: A Practical Approach to Microarray Data Analysis, D.P. Berrar, W. Dubitzky and M. Granzow (Eds.), Kluwer Academic Publishers, Boston, MA, Chapter 9, 166-185, 2003.

Mukherjee, S., P. Golland and D. Panchenko. Permutation Tests for Classification, AI Memo #2003-019, Massachusetts Institute of Technology, Cambridge, MA, August 2003.

Mukherjee, S., P. Tamayo, S. Rogers, R. Rifkin, A. Engle, C. Campbell, T.R. Golub and J.P. Mesirov. Estimating Dataset Size Requirements for Classifying DNA Microarray Data, Journal of Computational Biology, 2003, in press.

Nakajima, C., M. Pontil, B. Heisele and T. Poggio. Full-body Person Recognition System, Pattern Recognition, 36, 1997-2006, 2003.

Poggio, T. and S. Smale. The Mathematics of Learning: Dealing with Data, Notices of the American Mathematical Society (AMS), Vol. 50, No. 5, 537-544, 2003. (See journal issue at AMS Notices.)

Riesenhuber, M. and T. Poggio. How Visual Cortex Recognizes Objects: The Tale of the Standard Model. In: The Visual Neurosciences, (Eds. L.M. Chalupa and J.S. Werner), MIT Press, Cambridge, MA, Vol. 2, 1640-1653, 2003.

Rifkin, R., S. Mukherjee, P. Tamayo, S. Ramaswamy, C.-H. Yeang, M. Angelo, M. Reich, T. Poggio, E.S. Lander, T.R. Golub and J.P. Mesirov. An Analytical Method for Multi-class Molecular Cancer Classification, SIAM Reviews, Vol. 45, No. 4, 706-723, 2003.

Rifkin, R., G. Yeo and T. Poggio. Regularized Least Squares Classification. In: Advances in Learning Theory: Methods, Model and Applications, NATO Science Series III: Computer and Systems Sciences, VIOS Press, Amsterdam, (Eds.) Suykens, Horvath, Basu, Micchelli and Vandewalle, Vol. 190, Chapter 7, 131-154, 2003.

Rosen, E. Face Representation in Cortex: Studies Using a Simple and Not So Special Model, CBCL Paper #228/AI Technical Report #2003-010, Massachusetts Institute of Technology, Cambridge, MA, June 2003.

Rosen, Ezra (S.M. Thesis, EECS, MIT, May 2003): Face Representation in Cortex: Studies Using a Simple and Not So Special Model.

Sadr, J., I. Jarudi and P. Sinha. "The Role of Eyebrows in Face Recognition," Perception, 32, 285-293, 2003.

Shimizu, H. and T. Poggio. Direction Estimation of Pedestrain from Images, CBCL Paper #230/AI Memo #2003-020, Massachusetts Institute of Technology, Cambridge, MA, August 2003.

Yeo, G. and C. Burge. Maximum Entropy Modeling of Short Sequence Motifs with Applications to RNA Splicing Signals. In: Proceedings of the Seventh Annual International Conference on Research in Computational Molecular Biology, Berlin, Germany, April 10-13, 2003.

2002:

Bileschi, S.M. and B. Heisele. Advances in Component-based Face Detection. In: Proceedings of Pattern Recognition with Support Vector Machines, First International Workshop, SVM 2002, Niagara Falls, Canada, S.-W. Lee and A. Verri (eds.), Lecture Notes in Computer Science, Springer LNCS 2388, 135-143, 2002.

B\FClthoff, H.H., S.-W. Lee, T. Poggio and C. Wallraven (Eds.), Biologically Motivated Computer Vision, Proceedings of Second International Workshop, BMCV 2002, T\FCbingen, Germany, November 22-24, 2002, Vol. 2525 of Lecture Notes in Computer Science, Springer, New York, 2002.

Crane, A. (S.M. Thesis, EECS, MIT, September 2002): Object Recognition with Partially Labeled Examples.

Evgeniou, T., M. Pontil, C. Papageorgiou and T. Poggio. Image Representations and Feature Selection for Multimedia Database Search. In: IEEE Transactions in Knowledge and Data Engineering, May 2002, to appear.

Ezzat, A. (Ph.D. Thesis, EECS, MIT, June 2002): Trainable Videorealistic Speech Animation.

Ezzat, T., G. Geiger and T. Poggio. Trainable Videorealistic Speech Animation. In: Proceedings of ACM SIGGRAPH 2002, San Antonio, TX, 388-398, 2002.

Fahle, M. and T. Poggio (Eds.). Perceptual Learning, MIT Press, Cambridge, MA, 2002.

Freedman, D.J., M. Riesenhuber, T. Poggio, and E.K. Miller. Visual Categorization and the Primate Prefrontal Cortex: Neurophysiology and Behavior, Journal of Neurophysiology, 88, 930-942, 2002.

Giese, M.A. and T. Poggio. Biologically Plausible Neural Model for the Recognition of Biological Motion and Actions, CBCL Paper #219/AI Memo #2002-012, Massachusetts Institute of Technology, Cambridge, MA, August 2002.

Giese, M.A. and X. Xie. Exact Solution of the Nonlinear Dynamics of Recurrent Neural Mechanisms for Direction Selectivity, CBCL Paper #220/AI Memo #2002-013, Massachusetts Institute of Technology, Cambridge, MA, August 2002.

Heisele, B., T. Serre, M. Pontil, T. Vetter and T. Poggio. Categorization by Learning and Combining Object Parts. In: Advances in Neural Information Processing Systems 14, Vancouver, Canada, Vol. 2, 1239-1245, 2002.

Heisele, B., A. Verri and T. Poggio. Learning and Vision Machines. In: Proceedings of the IEEE, Visual Perception: Technology and Tools, Vol. 90, No. 7, 1164-1177, 2002.

Huang, J., V. Blanz and B. Heisele. Face Recognition Using Component-Based SVM Classification and Morphable Models. In: Proceedings of Pattern Recognition with Support Vector Machines, First International Workshop, SVM 2002, Niagara Falls, Canada, S.-W. Lee and A. Verri (eds.), Lecture Notes in Computer Science, Springer 2388, 334-341, 2002.

Kim, A.J. and Shelton, C.R. Modeling Stock Order Flows and Learning Market-Making from Data, CBCL Paper #217/AI Memo #2002-009, Massachusetts Institute of Technology, Cambridge, MA, June 2002.

Knoblich, U., D. Freedman and M. Riesenhuber. Categorization in IT and PFC: Model and Experiments, CBCL Paper #216/AI Memo #2002-007, Massachusetts Institute of Technology, Cambridge, MA, April 2002.

Knoblich, U. and M. Riesenhuber. Stimulus Simplification and Object Representation: A Modeling Study, CBCL Paper #215/AI Memo #2002-004, Massachusetts Institute of Technology, Cambridge, MA, March 2002.

Knoblich, U., M. Riesenhuber, D.J. Freedman, E.K. Miller and T. Poggio. Visual Categorization: How the Monkey Brain Does It. In: Biologically Motivated Computer Vision, Second International Workshop (BMCV 2002), T\FCbingen, Germany, 273-281, 2002.

Kreiman, G., I. Fried, and C. Koch. Single Neuron Correlates of Subjective Vision in the Human Medial Temporal Lobe, Proceedings of the National Academy of Sciences, USA 99, 8378-8383, 2002.

Kumar, V. (Ph.D. Thesis, BCS, MIT, June 2002): Towards Trainable Man-machine Interfaces: Combining Top-down Constraints with Bottom-up Learning in Facial Analysis.

Kumar, V.P. Towards Man-machine Interfaces: Combining Top-down Constraints with Bottom-up Learning in Facial Analysis, CBCL Paper #221/AI Technical Report #2002-008, Massachusetts Institute of Technology, Cambridge, MA, August 2002.

Mukherjee, S., P. Niyogi, T. Poggio and R. Rifkin. Statistical Learning: Stability is Sufficient for Generalization and Necessary and Sufficient for Consistency of Empirical Risk Minimization, CBCL Paper #223, Massachusetts Institute of Technology, Cambridge, MA, December 2002 [January 2004 revision].

Mukherjee, S., R. Rifkin and T. Poggio. Regression and Classification with Regularization. In: Lectures Notes in Statistics: Nonlinear Estimation and Classification, Proceedings from MSRI Workshop, D.D. Denison, M.H. Hansen, C.C. Holmes, B. Mallick and B. Yu (eds.), Springer-Verlag, 171, 107-124, 2002.

Papageorgiou, C., F. Girosi and T. Poggio. "Sparse Correlation Kernel Reconstruction and Superresolution." In: Probabilistic Models of the Brain - Perception and Neural Function, Rajesh Rao, Bruno Olshausen and Michael Lewicki (eds.), Cambridge, MA, The MIT Press, pp. 155-177, 2002.

Perez-Breva, L. and O. Yoshimi. Model Selection in Summary Evaluation, CBCL Paper #222/AI Memo #2002-023, Massachusetts Institute of Technology, Cambridge, MA, December 2002.

Poggio, T., S. Mukherjee, R. Rifkin, A. Rakhlin and A. Verri. B. In: Uncertainty in Geometric Computations, J. Winkler and M. Niranjan (eds.), Kluwer Academic Publishers, 131-141, 2002.

Poggio, T., R. Rifkin, S. Mukherjee and A. Rakhlin. Bagging Regularizes, CBCL Paper #214/AI Memo #2002-003, Massachusetts Institute of Technology, Cambridge, MA, February 2002.

Pollak, S. and P. Sinha. "Enhanced Perceptual Sensitivity for Anger among Physically Abused Children," Developmental Psychology, Vol. 38, No. 5, 784-791, 2002.

Pomeroy, S.L., P. Tamayo, M. Gaasenbeek, L.M. Sturia, M. Angelo, M.E. McLaughlin, J.Y.H. Kim, L.C. Goumnerova, P.M. Black, C. Lau, J.C. Allen, D. Zagzag, M.M. Olson, T. Curran, C. Wetmore, J.A. Biegel, T. Poggio, S. Mukherjee, R. Rifkin, A. Califano, G. Stolovitzky, D.N. Louis, J.P. Mesirov, E.S. Lander and T.R. Golub. Prediction of Central Nervous System Embryonal Tumour Outcome Based on Gene Expression, Nature (Letters to Nature), Vol. 415, 436-442, 2002.

Rakhlin, A., G. Yeo and T. Poggio. Extra-label Information: Experiments with View-based Classification. In: Proceedings of the Sixth International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES'2002), Podere d'Ombriano, Crema, Italy, September 16-18, 2002.

Riesenhuber, M. and T. Poggio. Neural Mechanisms of Object Recognition, Current Opinion in Neurobiology, 12, 162-168, 2002.

Rifkin, R. (Ph.D. Thesis, EECS & OR, MIT, September, 2002): Everything Old Is New Again: A Fresh Look at Historical Approaches in Machine Learning.

Sadr, J. and P. Sinha. "Assessing Visual function using Random Image Structure Evolution," Cognitive Science, 2002 (to appear).

Sadr, J., S. Mukherjee, K. Thoresz, and P. Sinha. "The Fidelity of Local Ordinal Encodings." In: Advances in Neural Information Processing Systems, MIT Press, 2002.

Schneider, R. and M. Riesenhuber. A Detailed Look at Scale and Translation Invariance in a Hierarchical Neural Model of Visual Object Recognition, CBCL Paper #218/AI Memo #2002-011, Massachusetts Institute of Technology, Cambridge, MA, August 2002.

Serre, T., M. Riesenhuber, J. Louie, and T. Poggio. On the Role of Object-Specific Features for Real World Object Recognition in Biological Vision. In: Biologically Motivated Computer Vision, Second International Workshop (BMCV 2002), T\FCbingen, Germany, 387-397, 2002.

Sinha, P. "Identifying Perceptually Significant Features for Recognizing Faces." In: Proceedings of the SPIE Electronic Imaging 2002 Symposium - Electronic Imaging Systems and Image Processing Methods, Human Vision and Electronics Imaging VII, January 21-24, 2002.

Sinha, P. "Neurally Inspired Strategies for Face, Voice and Handwriting Recognition," Nature Neuroscience, 2002 (to appear).

Sinha, P. and T. Poggio. "High-level Learning of Early Perceptual Tasks." In: Perceptual Learning, (ed. Manfred Fahle), MIT Press, Cambridge, MA, 2002.

Sinha, P. and T. Poggio. United We Stand: The Role of Head Structure in Face Recognition, Perception, 31/1, 133, 2002.

Szummer, M. (Ph.D. Thesis, EECS, MIT, September 2002): Learning from Partially Labeled Data.

Walther, D., L. Itti, M. Riesenhuber, T. Poggio, and C. Koch. Attentional Selection for Object Recognition \96 A Gentle Way. In: Biologically Motivated Computer Vision, Second International Workshop (BMCV 2002), T\FCbingen, Germany, 472-479, 2002.

Weinstein, E., P. Ho, B. Heisele, T. Poggio, K. Steele and A. Agarwal. Handheld Face Identification Technology in a Pervasive Computing Environment. In: Proceedings of Pervasive 2002, Zurich, Switzerland, August 26-28, 48-54, 2002.

Yip, A. and P. Sinha. "Role of Color in Face Recognition," Perception, Vol. 31, 995-1003, 2002.

Yu, A.J., M.A. Giese and T. Poggio. "Biophysiologically Plausible Implementations of the Maximum Operation," Neural Computation, Vol. 14, No. 12, 2857-2881, 2002.

2001:

Alvira, M., J. Paris and Rifkin, R. The Audiomomma Music Recommendation System, CBCL Paper #199/AI Memo #2001-012, Massachusetts Institute of Technology, Cambridge, MA, July 2001.

Alvira, M. and Rifkin, R. An Empirical Comparison of SNoW and SVMs for Face Detection, CBCL Paper #193/AI Memo #2001-004, Massachusetts Institute of Technology, Cambridge, MA, January 2001.

Cauwenberghs, G. and T. Poggio. Incremental and Decremental Support Vector Machine Learning. In: Advances in Neural Information Processing Systems (NIPS*2000), MIT Press, Vol. 13, 409-415, Cambridge, MA, 2001.

Chan, Nicholas (Ph.D. Thesis, EECS, MIT, February 2001): Artificial Markets and Intelligent Agents.

Chan, N.T., B. LeBaron, A.W. Lo and T. Poggio. Agent-Based Models of Financial Markets: A Comparison with Experimental Markets, MIT Sloan Working Paper No. 4195-01, Social Science Research Network Electronic Library, October 2001.

Chan, N., E. Dahan, A. Lo and T. Poggio. Experimental Markets for Product Concepts, CBCL Paper #200/AI Memo #2001-013, Massachusetts Institute of Technology, Cambridge, MA, July 2001.

Chan, N. and C. Shelton. An Electronic Market-Maker, CBCL Paper #195/AI Memo #2001-005, Massachusetts Institute of Technology, Cambridge, MA, April 2001.

Chapelle, O., V. Vapnik, O. Bousquet and S. Mukherjee. Choosing Multiple Parameters for Support Vector Machines, Machine Learning - Special Issue on Support Vector Machines, 2001.

Evgeniou, T. and M. Pontil. A Note on the Generalization Performance of Kernel Classifiers with Margin. In: Proceedings of Algorithmic Learning Theory 2000 Conference, Lecture Notes in Artificial Intelligence, Sydney, Australia (December 11-13, 2000), Vol. 1968, 306-315, 2001.

Freedman, D.J., M. Riesenhuber, T. Poggio and E.K. Miller. Categorical Representation of Visual Stimuli in the Primate Prefrontal Cortex, Science, 291, 312-316, 2001.

Heisele, B., P. Ho and T. Poggio. Face Recognition with Support Vector Machines: Global Versus Component-based Approach, International Conference on Computer Vision (ICCV'01), Vancouver, Canada, Vol. 2, 688-694, 2001.

Heisele, B., T. Serre, M. Pontil and T. Poggio. Component-based Face Detection. In: Proceedings of 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), IEEE Computer Society Press, Kauai, Hawaii, Vol. 1, 657-662, December 2001.

Heisele, B., T. Serre, S. Mukherjee and T. Poggio. Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images. In: Proceedings of 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), IEEE Computer Society Press, Kauai, Hawaii, Vol. 2, 18-24, December 2001.

Ho, P. Rotation Invariant Real-time Face Detection and Recognition System, CBCL Paper #197/AI Memo #2001-010, Massachusetts Institute of Technology, Cambridge, MA, May 2001.

Ho, Purdy (S.M. Thesis, EECS, MIT, May 2001): "Rotation Invariant Realtime Face Detection and Recognition System."

Mohan, A., C. Papageorgiou and T. Poggio. Example-based Object Detection in Images by Components, IEEE (PAMI), Vol. 23, No. 4, 349-361, April 2001.

Mukherjee, Sayan (Ph.D. Thesis, BCS, MIT, June 2001): Application of Statistical Learning Theory to DNA Microarray Analysis.

Ostrovsky, Y., P. Cavanagh and P. Sinha. Perceiving Illumination Inconsistencies in Scenes, CBCL Paper #209/AI Memo #2001-029, Massachusetts Institute of Technology, Cambridge, MA, November 2001.

Peshkin, L. and S. Mukherjee. Bounds on Sample Size for Policy Evaluation in Markov Environments. In: Proceedings of COLT 2001: The Fourteenth Annual Conference on Computational Learning Theory 2001, Amsterdam, Netherlands (July 16-19, 2001), to appear.

Poggio, T., S. Mukherjee, R. Rifkin, A. Rakhlin and A. Verri. b, CBCL Paper #198/AI Memo #2001-011, Massachusetts Institute of Technology, Cambridge, MA, July 2001.

Ramaswamy, S., P. Tamayo, R. Rifkin, S. Mukherjee, C.-H. Yeang, M. Angelo, C. Ladd, M. Reich, E. Latulippe, J.P. Mesirov, T. Poggio, W. Gerald, M. Loda, E.S. Lander, and T.R. Golub. Multiclass Cancer Diagnosis Using Tumor Gene Expression Signatures, PNAS, Vol. 98, No. 26, 15149-15154, December 2001.

Rennie, J.D.M. and R. Rifkin. Improving Multiclass Text Classification with the Support Vector Machine, CBCL Paper #210/AI Memo #2001-026, Massachusetts Institute of Technology, Cambridge, MA, October 2001.

Riesenhuber, M. Generalization Over Contrast and Mirror Reversal, but Not Figure-ground Reversal, in an "Edge-based" Model of IT Neurons, CBCL Paper #211/AI Memo #2001-034, Massachusetts Institute of Technology, Cambridge, MA, December 2001.

Russell, R. and P. Sinha. Perceptually-based Comparison of Image Similarity Metrics, CBCL Paper #201/AI Memo #2001-014, Massachusetts Institute of Technology, Cambridge, MA, July 2001.

Sadr, J. and P. Sinha. Exploring Object Perception with Random Image Structure Evolution, CBCL Paper #196/AI Memo #2001-006, Massachusetts Institute of Technology, Cambridge, MA, March 2001.

Shelton, C. Importance Sampling for Reinforcement Learning with Multiple Objectives, CBCL Paper #204/AI Technical Report #2001-003, Massachusetts Institute of Technology, Cambridge, MA, August 2001.

Shelton, C. Balancing Multiple Sources of Reward in Reinforcement Learning. In: Advances in Neural Information Processing Systems (NIPS), 1082-1088, 2001.

Shelton, C. Policy Improvement for POMDPs Using Normalized Importance Sampling, CBCL Paper #194/AI Memo #2001-002, Massachusetts Institute of Technology, Cambridge, MA, March 2001.

Sinha, P. and A. Torralba. Role of Low-level Mechanisms in Brightness Perception, CBCL Paper #203/AI Memo #2001-017, Massachusetts Institute of Technology, Cambridge, MA, August 2001.

Torralba, A. and A. Oliva. Global Depth Perception from Familiar Scene Structure, CBCL Paper #213/AI Memo #2001-036, Massachusetts Institute of Technology, Cambridge, MA, December 2001.

Torralba, A. and P. Sinha. Detecting Faces in Impoverished Images, CBCL Paper #208/AI Memo #2001-028, Massachusetts Institute of Technology, Cambridge, MA, November 2001.

Torralba, A. and P. Sinha. "Contextual Priming for Object Recognition." In: Proceedings of the IEEE International Conference on Computer Vision, Vancouver, Canada, 2001.

Torralba, A. and P. Sinha. Contextual Priming for Object Detection, CBCL Paper #205/AI Memo #2001-020, Massachusetts Institute of Technology, Cambridge, MA, September 2001.

Torralba, A. and P. Sinha. Recognizing Indoor Scenes, CBCL Paper #202/AI Memo #2001-015, Massachusetts Institute of Technology, Cambridge, MA, July 2001.

Vaina, L.M., J. Solomon, S. Chowdry, P. Sinha, J.W. Belliveau, and C.G. Gross. "Functional Neuroanatomy of Biological Motion Perception in Humans." In: Proceedings of the National Academy of Sciences, 98, 11656-11661, 2001.

Weston, J., S. Mukherjee, O. Chapelle, M. Pontil, T. Poggio and V. Vapnik. Feature Selection for SVMs. In: Advances in Neural Information Processing Systems (NIPS), 13, 668-674, 2001.

Yeang, C.-H., S. Ramaswamy, P. Tamayo, S. Mukherjee, R.M. Rifkin, M. Angelo, M. Reich, E. Lander, J. Mesirov, and T. Golub. Molecular Classification of Multiple Tumor Types. In: Intelligent Systems in Molecular Biology - Bioinformatics Discovery Note, Proceedings of the Ninth International Conference on Intelligent Systems in Molecular Biology, Copenhagen, Denmark, (July 21-25, 2001), Vol. 1, No. 1, S316-S322, 2001.

Yeo, G. and T. Poggio. Multiclass Classification of SRBCTs, CBCL Paper #206/AI Memo #2001-018, Massachusetts Institute of Technology, Cambridge, MA, August 2001.

Yip, A. and P. Sinha. Role of Color in Face Recognition, CBCL Paper #212/AI Memo #2001-035, Massachusetts Institute of Technology, Cambridge, MA, December 2001.

Yu, A., M.A. Giese and T. Poggio. Biological Plausible Neural Circuits for Realization of the Maximum Operations, CBCL Paper #207/AI Memot #2001-022, Massachusetts Institute of Technology, Cambridge, MA, September 2001.

2000:

Evgeniou, T. (Ph.D. Thesis, EECS, MIT, June 2000): Learning with Kernel Machine Architectures.

De Mori, R. and T. Poggio. "Information Retrieval e Biblioteche Digitali," Technology Review: Edizione Italiana, 13, 1, 46-51, 2000.

Evgeniou, T., M. Pontil and T. Poggio. Statistical Learning Theory: A Primer, International Journal of Computer Vision, 38, 1, 9-13, 2000.

Evgeniou, T., L. Perez-Breva, M. Pontil, and T. Poggio. Bounds on the Generalization Performance of Kernel Machine Ensembles. In: Proceedings of Seventeenth International Conference on Machine Learning, Stanford University, June 29-July 2, 2000, (to appear).

Evgeniou, T., M. Pontil and T. Poggio. Regularization Networks and Support Vector Machines, Advances in Computational Mathematics, 13, 1, 1-50, 2000.

Ezzat, T. and T. Poggio. Visual Speech Synthesis by Morphing Visemes, International Journal of Computer Vision, 38, 1, 45-57, 2000.

Ezzat, T. and T. Poggio. Visual Speech Synthesis by Morphing Visemes. In: NTT R&D, 49, 7, 372-375, 2000.

Giese, M.A. Neural Model for the Recognition of Biological Motion. In: Dynamische Perzeption, G. Baratoff and H. Neumann (eds.), Infix Verlag, Berlin, 105-110, 2000.

Giese, M.A. Neural Field Model for the Recognition of Biological Motion Patterns. In: Second International ICSC Symposium on Neural Computation, Berlin, Germany, May 23-26, 2000.

Giese, M.A. and T. Poggio. Quantification and Classification of Locomotion Patterns by Spatio-temporal Morphable Models. In: Third IEEE Workshop on Visual Surveillance, Dublin, Ireland, July 1, 2000.

Giese, M.A. and T. Poggio. Morphable Models for the Analysis and Synthesis of Complex Motion Pattern, International Journal of Computer Vision, 38, 1, 59-73, 2000.

Heisele, B., T. Poggio and M. Pontil. Face Detection in Still Gray Images, CBCL Paper #187/AI Memo #1687, Massachusetts Institute of Technology, Cambridge, MA, June 2000.

Kumar, V. and T. Poggio. Learning-based Approach to Estimation of Morphable Model Parameters, CBCL Paper #191/AI Memo #1696, Massachusetts Institute of Technology, Cambridge, MA, September 2000.

Kumar, V. and T. Poggio. Learning-based Approach to Real Time Tracking and Analysis of Faces. In: Proceedings of the Fourth International Conference on Face and Gesture Recognition, Grenoble, France, 91-96, March, 2000.

Lee, S-W., H.H. Buelthoff and T. Poggio (eds.), Biologically Motivated Computer Vision, First IEEE International Workshop, BMCV 2000, Seoul, Korea, May 2000.

Nakajima, C., I. Norihiko, M. Pontil and T. Poggio. Object Recognition and Detection by a Combination of Support Vector Machine and Rotation Invariant Phase Only Correlation. In: Proceedings of International Conference on Pattern Recognition, Barcelona, Spain, September 2000.

Nakajima, C., M. Pontil and T. Poggio. People Recognition and Pose Estimation in Image Sequences. In: Proceedings of IEEE-INNS-ENNS International Joint Conference on Neural Networks, Como, Italy, July 2000.

Nakajima, C., M. Pontil, B. Heisele and T. Poggio. People Recognition in Image Sequences by Supervised Learning, CBCL Paper #188/AI Memo #1688, Massachusetts Institute of Technology, Cambridge, MA, June 2000.

Papageorgiou, C. A Trainable System for Object Detection in Images and Video Sequences, CBCL Paper #186/AI Tech Report #1685, Massachusetts Institute of Technology, Cambridge, MA, May 2000.

Papageorgiou, C. and T. Poggio. A Trainable System for Object Detection, International Journal of Computer Vision, 38, 1, 15-33, 2000.

Poggio, T. "Second Wave of Network Technologies," The Future of Software, 1, 1, 84-85, Winter 2000/2001.

Poggio, T. and C. Shelton. "Learning in Brains and Machines," Spatial Vision, Vol. 13, No. 2-3, 287-296, 2000.

Poggio, T. and A. Verri. Introduction: Learning and Vision at CBCL, International Journal of Computer Vision, 38, 1, 5-7, 2000.

Pontil, M., S. Mukherjee, and F. Girosi. On the Noise Model of Support Vector Machine Regression. In: Proceedings of Algorithmic Learning Theory 2000 Conference, Sydney, Australia, December 11-13, 2000, (to appear).

Riesenhuber, M. (Ph.D. Thesis, BCS, MIT, June 2000): How a Part of the Brain Might or Might Not Work: A New Hierarchical Model of Object Recognition.

Riesenhuber, M., and T. Poggio. Models of Object Recognition, Nature Neuroscience, 3 Supp., 1199-1204, 2000.

Riesenhuber, M. and T. Poggio. Computational Models of Object Recognition in Cortex: A Review, CBCL Paper #190/AI Memo #1695, Massachusetts Institute of Technology, Cambridge, MA, August 2000.

Riesenhuber, M. and T. Poggio. "CBF: A New Framework for Object Categorization in Cortex." In: Biologically Motivated Computer Vision, Lee, S-W., H.H. Buelthoff and T. Poggio (eds.), First IEEE International Workshop, BMCV 2000, Seoul, Korea, May 2000.

Riesenhuber, M. and T. Poggio. The Individual is Nothing, the Class Everything: Psychophysics and Modeling of Recognition in Object Classes, CBCL Paper #185/AI Memo #1682, Massachusetts Institute of Technology, Cambridge, MA, April 2000.

Serre, T. (Graduate Engineering degree, Ecole Nationale Sup\E9rieure des T\E9l\E9communications de Bretagne, October 2000): "Feature Selection for Face Detection in Still Gray Images."

Serre, T., B. Heisele, S. Mukherjee and T. Poggio. Feature Selection for Face Detection, CBCL Paper #192/AI Memo #1697, Massachusetts Institute of Technology, Cambridge, MA, September 2000.

Shelton, C. Morphable Surface Models, International Journal of Computer Vision, 38, 1, 75-91, 2000.

Sinha, P. "The Perception of Gaze Direction," Perception, 2000 (to appear).

Sinha, P. and T. Poggio. "High-level Learning of Early Perceptual Tasks." In: Perceptual Learning, (Ed). Manfred Fahle, MIT Press, Cambridge, MA, 2000 (to appear).

1999:

Bizzi, E. and F.A. Mussa-Ivaldi. "Toward a Neurobiology of Coordinate Transformations." In: Cognitive Neuroscience, MIT Press, 2000.

Bizzi, E., P. Saltiel and M.C. Tresch. "Spinal Cord Modules and the Organization of Motor Behavior," Neuron, 1999, in press.

Dinse, H.R., Jancke, D., Akhavan, A.C., Kalt, T., Giese, M.A. and Sch\F6ner, G. "Dynamic Population Representations of the Visual and Somatosensory Cortex." In: Proceedings of the International Conference on Neural Information Processing 96, S. Amari, L. Xu, L. Chan, I. King, K. Leung (eds.), Springer, NY, 1285-1290, 1999.

Evgeniou, T. and M. Pontil. On the V Gamma Dimension for Regression in Reproducing Kernel Hilbert Spaces, CBCL Paper #172/AI Memo #1656, Massachusetts Institute of Technology, Cambridge, MA, May 1999.

Evgeniou, T., M. Pontil, and T. Poggio. A Unified Framework for Regularization Networks and Support Vector Machines, CBCL Paper #171/AI Memo #1654, Massachusetts Institute of Technology, Cambridge, MA, March 1999.

Ezzat, T. and T. Poggio. Visual Speech Synthesis by Morphing Visemes, CBCL Paper #173/AI Memo #1658, Massachusetts Institute of Technology, Cambridge, MA, May 1999.

Giese, M.A. "Quick Work but Variable Quality," Nature, 401, 13, 1999.

Giese, M.A. Evidence for Multi-functional Interactions in Early Visual Motion Processing, Trends in Neurosciences, Vol. 22, No. 7, 287-290, 1999.

Giese, M.A. Dynamic Neural Field Theory of Motion Perception, Kluwer Academic Publishers, Dordrecht, Netherlands, 1999.

Giese, M.A., and T. Poggio. Synthesis and Recognition of Biological Motion Patterns Based on Linear Superposition of Prototypical Motion Sequences. In: Proceedings of the IEEE Workshop on Multi-View Modeling and Analysis of Visual Scene, Fort Collins, CO, 73-80, 1999.

Jaakkola, T., and M.I. Jordan. "Bayesian Logistic Regression: A Variational Approach," Statistics and Computing, in press.

Jaakkola, T. and M.I. Jordan. "Variational Probabilistic Inference and the QMR-DT Network," Journal of Artificial Intelligence Research, 10, 291-322, 1999.

Jaakkola, T., and M.I. Jordan. "Variational Methods and the QMR-DT Database." In: Neural Networks and Machine Learning, C. M. Bishop (Ed.), Berlin: Springer-Verlag, 1999.

Jancke, D., Erlhagen, W., Dinse, H.R., Akhavan, A.C., Giese, M.A, Steinhage, A. and Sch\F6ner, G. "Population Representation of Retinal Position in Cat Primary Visual Cortex: Interaction and Dynamics," Journal of Neuroscience, 22, 287-290, 1999.

Jordan, M. I. (Ed.). Learning in Graphical Models, Cambridge, MA, MIT Press, 1999.

Jordan, M. I., and D. M. Wolpert. "Computational Motor Control." In: The Cognitive Neurosciences, 2nd edition, M. Gazzaniga (Ed.), Cambridge, MA, MIT Press, 1999.

Jordan, M. I., Z. Ghahramani, T.S. Jaakkola and L.K. Saul. "An Introduction to Variational Methods for Graphical Models," Machine Learning, in press.

Koch, C. and T. Poggio. "Predicting the Visual World: Silence is Golden," Nature Neuroscience, Vol. 2, No. 1, 9-10, January 1999.

Kumar, V. and T. Poggio. Learning-based Approach to Real-time Tracking and Analysis of Faces, CBCL Paper #179/AI Memo #1672, Massachusetts Institute of Technology, Cambridge, MA, September 1999.

Loeb, E., S. Giszter, P. Saltiel, F.A. Mussa-Ivaldi and E. Bizzi. "Output Units of Motor Behavior: An Experimental and Modeling Study," J. Cognitive Neuroscience, 1999, in press.

Meila, M. An Accelerated Chow and Liu Algorithm: Fitting Tree Distributions to High Dimensional Sparse Data, CBCL Paper #169/AI Memo #1652, Massachusetts Institute of Technology, Cambridge, MA, 1999.

Marques, J. (S.M. Thesis, EECS, MIT, May 1999): "An Automatic Annotation System for Audio Data Containing Music."

Mohan, A. (S.M. Thesis, EECS, MIT, June 1999): "Robust Object Detection in Images by Computers."

Mohan, A. Object Detection in Images by Components, CBCL Paper #178/AI Memo #1664, Massachusetts Institute of Technology, Cambridge, MA, June 1999.

Mukherjee, S., P. Tamayo, J.P. Mesirov, D. Slonim, A. Verri and T. Poggio. Support Vector Machine Classification of Microarray Data, CBCL Paper #182/AI Memo #1677, Massachusetts Institute of Technology, Cambridge, MA, December 1999.

Mukherjee, S. and V. Vapnik. Multivariate Density Estimation: An SVM Approach, CBCL Paper #170/AI Memo #1653, Massachusetts Institute of Technology, Cambridge, MA, April 1999.

Niyogi, P. and F. Girosi. Generalization Bounds for Function Approximation from Scattered Noisy Data, Advances in Computational Mathematics, Vol. 10, 51-80, 1999.

Papageorgiou, Constantine (Ph.D. Thesis, EECS, MIT, December 1999): A Trainable System for Object Detection in Images and Video Sequences.

Papageorgiou, C. and T. Poggio. A Trainable Object Detection System: Car Detection in Static Images, CBCL Paper #180/AI Memo #1673, Massachusetts Institute of Technology, Cambridge, MA, April 1999.

Papageorgiou, C. and T. Poggio. Trainable Pedestrian Detection, International Conference on Image Processing (ICIP'99), Kobe, Japan, October 1999.

Papageorgiou, C. and T. Poggio. A Pattern Classification Approach to Dynamical Object Detection. In: Proceedings of International Conference on Computer Vision (ICCV'99), Corfu, Greece, 1223-1228, September 1999.

Papageorgiou, C., F. Girosi and T. Poggio. Sparse Correlation Kernel Reconstruction. In: Proceedings of International Conference on Acoustics, Speech, and Signal Processing, Phoenix, AZ, 1633-1636, March 1999.

P\E9rez-Breva, L. (Ingenieria Superior, Institut Quimic de Sarri\E0, Universitat Ramon Llull, Barcelona, July 1999): \93Applying Learning Techniques to Solve Engineering Problems: Preprocessing, Learning and Measuring.\94

Poggio, T. "Imparare a Vedere." In: Enciclopedia Italiana Treccani, III, 675-685, 1999.

Poggio, T. and C. Shelton. Machine Learning, Machine Vision and the Brain, AI Magazine, Vol. 20, No. 3, 37-55, 1999.

Rachlevsky-Reich, B., I. Ben-Shaul, N. Tung Chan, A. Lo and T. Poggio. GEM: A Global Electronic Market System, Information Systems, Vol. 24, No. 6, p. 495-518, 1999.

Riesenhuber, M. and T. Poggio. A Note on Object Class Representation and Categorical Perception, CBCL Paper #183/AI Memo #1679, Massachusetts Institute of Technology, Cambridge, MA, December 1999.

Riesenhuber, M. and T. Poggio. Hierarchical Models of Object Recognition in Cortex, Nature Neuroscience, 2, 1019-1025, 1999.

Riesenhuber, M. and T. Poggio. Are Cortical Models Really Bound by the 'Binding Problem'?, Neuron 24, 87-93, 1999.

Rifkin, R., M. Pontil and A. Verri. A Note on Support Vector Machines Degeneracy, CBCL Paper #177/AI Memo #1661, Massachusetts Institute of Technology, Cambridge, MA, June 1999.

Saul, L. K., and M.I. Jordan. "Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixture of Simpler Ones," Machine Learning, in press.

Tresch, M.C., P. Saltiel and E. Bizzi. "The Construction of Movement by the Spinal Cord," Nature Neuroscience, 2:162-167, 1999.

Tresch, M.C. and E. Bizzi. "Movements evoked from microstimulation of the Spinal Cord in the Chronically Spinalized Rat: Basic Characteristics and Relationship to Spinal Cutaneous Systems," Exp. Brain Research, 1999, in press.

Wang, Jon (S.M. Thesis, EECS, MIT, May 1999): "Information Aggregation and Dissemination in Simulated Markets."

1998:

Bizzi, E. and F.A. Mussa-Ivaldi. "Neural Basis of Motor Control and Its Cognitive Implication," Trends in Cognitive Science, 2 3: 97-102, 1998.

Bizzi, E. and F.A. Mussa-Ivaldi. "The Acquisition of Motor Behavior," Daedalus, 127: 217-232, 1998.

Bizzi, E., P. Saltiel and M.C. Tresch. "Modular Organization of Motor Behavior," Zeitschrift für Naturforschung, 53c: 510-517, 1998.

Bishop, C. M., N. Lawrence, T.S. Jaakkola and M.I. Jordan. "Approximating Posterior Distributions in Belief Networks using Mixtures." In: Advances in Neural Information Processing Systems 10, Jordan, M. I., Kearns, M. J. and Solla, S. A. (Eds.), Cambridge MA: MIT Press, 1998.

Chan, N., B. LeBaron, A. Lo and T. Poggio. Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders, CBCL Paper #164/AI Memo #1646, Massachusetts Institute of Technology, Cambridge, MA, September 1998.

Chellappa, R., K. Fukushima, A.K. Katsaggelos, S-Y. Kung,\A0 Y. LeCun, N.M. Nasrabadi, T. Poggio.\A0 Applications of Artificial Neural Networks to Image Processing, Guest Editorial for em>IEEE Transactions on Image Processing: Special Issue on Applications of Artificial Neural Networks to Image Processing, Volume 7, Number 8, August 1998.

D'Avella, A. and E. Bizzi. "Low Dimensionality of Supraspinally Induced Force Fields," Proc. of the National Academy of Science, 95: 7711-7714, 1998.

Ezzat, T. and T. Poggio. MikeTalk: A Talking Facial Display Based on Morphing Visemes. In: Proceedings of the Computer Animation Conference, Philadelphia, PA, 96-102, June 1998.

Finn, P., Kavraki, L., Latombe, J.C., Motwani, R., Shelton, C., Venkatasubramanian, S. and Yao, A. RAPID: Randomized Pharmacophore Identification for Drug Design, Computational Geometry: Theory and Applications, Vol. 10, No. 4, 1998.

Giese, M.A. "Dynamic Neural Field Model Links Neural and Computational Theories of Motion Perception." In: Workshop Dynamische Perzeption, Infix Verlag, H. Ritter and S. Posch (eds.), St. Augustin, Germany, 1998.

Girosi, F. An Equivalence between Sparse Approximation and Support Vector Machines, Neural Computation, Vol. 10, 1455-1480, 1998.

Giszter, S., E. Loeb, F.A. Mussa-Ivaldi and E. Bizzi. "Spatial Maps of Forces and Muscle Activity in Lumbar Spinal Cord of the Spinal Frog Elicited by microstimulation," Exp. Brain Research, submitted, 1998.

Halperin, D. and Shelton, C.R. "A Perturbation Scheme for Spherical Arrangements with Application to Molecular Modeling," Computational Geometry: Theory and Applications, Vol. 10, No. 4, 273-288, 1998.

Hofmann, Thomas and Jan Puzicha. Statistical Models for Co-occurrence Data, CBCL Paper #161/AI Memo #1625, Massachusetts Institute of Technology, Cambridge, MA, February 1998.

Houde, J. and M.I. Jordan. "Adaptation in Speech Production," Science, 279, 1213-1216, 1998.

Houde, J. and M.I. Jordan. "Adaptation in Speech Motor Control." In: Advances in Neural Information Processing Systems 10, Jordan, M. I., Kearns, M. J. and Solla, S. A. (Eds.), Cambridge MA: MIT Press, 1998.

Jaakkola, T. S., and M.I. Jordan. "Improving the Mean Field Approximation Via the Use of Mixture Distributions." In: Learning in Graphical Models, M. I. Jordan (Ed.), Cambridge, MIT Press, 1998.

Jones, M. and T. Poggio. Hierarchical Morphable Models. In: Proceedings of Computer Vision and Pattern Recognition, Santa Barbara, 820-826, June 23-25, 1998.

Jones, M. and T. Poggio. Multidimensional Morphable Models. In: Proceedings of the Sixth International Conference on Computer Vision, Bombay, India, 683-688, January 4-7, 1998.

Jones, M. and T. Poggio. Multidimensional Morphable Models: A Framework for Representing and Matching Object Classes, International Journal of Computer Vision, Vol. 29, No. 2, 107-131, 1998.

Jordan, M. I., Z. Ghahramani, T.S. Jaakkola and L.K. Saul. "An Introduction to Variational Methods for Graphical Models." In: Learning in Graphical Models, M. I. Jordan (Ed.), Cambridge, MIT Press, 1998.

Jordan, M. I., Kearns, M. J. and Solla, S. A. (Eds.). In: Advances in Neural Information Processing Systems 10, MIT Press, Cambridge MA, 1998.

Lawrence, N. D., C.M. Bishop, M.I. Jordan and T.S. Jaakkola. "Mixture representations for Inference and Learning in Boltzmann Machines." In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, G. F. Cooper and S. Moral (eds.), Morgan Kaufmann, San Mateo, CA, 1998.

Lemay, M.A., J.E. Galagan, N. Hogan and E. Bizzi. "Recruitment Properties of Spinal Cord Force Fields in the Spinalized Frog," IEEE TRE BME, submitted in 1998.

Li, Zhaoping. Pre-attentive Segmentation in the Primary Visual Cortex, CBCL Paper #163/AI Memo #1640, Massachusetts Institute of Technology, Cambridge, MA, April 1998.

Massberg, W., Weigt, D., Giese, M.A., Steinhage, A.and Sch\F6ner G. "Selbstorganisierende Fertigungssteuerung: Selbstorganisierendes Modell der Fertigungssteuerung auf der Basis Neuronaler Dynamik," WT Werkstatt Technik, Vol. 78, No. 98, 329-332, 1998.

Massberg, W., Weigt, D., Giese, M.A., Steinhage, A. and Sch\F6ner, G. "Modelle der Fertigungssteuerung: M\F6glichkeiten und Grenzen bestehender Modelle der Fertigungssteuerung," WT Werkstatt Technik, Vol. 3, No. 98, 97-100, 1998.

Meila, M. and M.I. Jordan. "Estimating Dependency Structure as a Hidden Variable." In: Advances in Neural Information Processing Systems 10, Jordan, M. I., Kearns, M. J. and Solla, S. A. (Eds.), Cambridge MA: MIT Press, 1998.

Niyogi, P., T. Poggio, and F. Girosi. Incorporating Prior Information in Machine Learning by Creating Virtual Examples. In: IEEE Proceedings on Intelligent Signal Processing, Vol. 86, No 11, 2196-2209, 1998.

Osuna, E. (Ph.D. Thesis, EECS & OR, MIT, June 1998): "Support Vector Machines: Training and Applications."

O'Toole, A.J., T. Vetter, N.F. Toje and H.H. Bülthoff. "Sex Classification is Better with Three-Dimensional Head Structure than with Texture," Perception, in press.

Papageorgiou, C., F. Girosi and T. Poggio. Sparse Correlation Kernel Analysis and Reconstruction , CBCL Paper #162/AI Memo #1635, Massachusetts Institute of Technology, Cambridge, MA, May 1998.

Papageorgiou, C. Mixed Memory Markov Models for Time Series Analysis. In: Proceedings of Computational Intelligence for Financial Engineering, New York, 165-170, March 1998.

Papageorgiou, C., M. Oren, and T. Poggio. A General Framework for Object Detection. In: Proceedings of the Sixth International Conference on Computer Vision (ICCV'98), Bombay, India, 555-562, January 1998.

Papageorgiou, C., T. Evgeniou, and T. Poggio. A Trainable Pedestrian Detection System. In: Proceedings of Intelligent Vehicles, Stuttgart, Germany, 241-246, 1998.

Poggio, T. and F. Girosi. A Sparse Representation for Function Approximation, Neural Computation, Vol. 10, No. 6, 1445-14454, 1998.

Poggio, T. and F. Girosi. Notes on PCA, Regularization, Sparsity and Support Vector Machines, CBCL Paper #161/AI Memo #1632, Massachusetts Institute of Technology, Cambridge, MA, April 1998.

Pontil, M. and A. Verri. Object Recognition with Support Vector Machines. In: IEEE Trans. Pattern Anal. Mach. Intell., Vol. 20, 637-646, 1998.

Pontil, M. and A. Verri. Properties of Support Vector Machines, Neural Computation, Vol. 10, pp. 955-974, 1998.

Pontil, M., R. Rifkin and T. Evgeniou. From Regression to Classification in Support Vector Machines, CBCL Paper #166, AI Memo #1649, Massachusetts Institute of Technology, Cambridge, MA, November 1998.

Pontil, M., S. Mukherjee and F. Girosi. On the Noise Model of Support Vector Machine Regression, CBCL Paper #168, AI Memo #1651, Massachusetts Institute of Technology, Cambridge, MA, October 1998.

Riesenhuber, M. and T. Poggio. Modeling Invariances in Inferotemporal Cell Tuning, CBCL Paper #160/AI Memo #1629, Massachusetts Institute of Technology, Cambridge, MA, March 1998.

Riesenhuber, M. and T. Poggio. Just One View: Invariances in Inferotemporal Cell Tuning. In: Advances in Neural Information Processing Systems, MIT Press, 10, 215-221, 1998.

Riesenhuber, M., H.U. Bauer, D. Brockmann, and T. Geisel. Breaking Rotational Symmetry in a Self-Organizing Map-Model for Orientation Map Development, Neural Computation, 10, 717-730, 1998.

Sabes, P., M.I. Jordan and D.M. Wolpert. "The Role Inertial Sensitivity in Motor Planning." Journal of Neuroscience, 18, 5948-5959, 1998.

Saltiel, P., M.C. Tresch and E. Bizzi. "Spinal Cord Modular Organization and Rhythm Generation: An NMDA Iontophoretic Study in the Frog," J. Neurophysiol., 80: 2323-2339, 1998.

Saul, L. K., and M. Jordan. "A Mean field Learning Algorithm for Unsupervised Neural Networks." In: Learning in Graphical Models, M. I. Jordan (Ed.), Cambridge: MIT Press, 1998.

Shelton, C. (S.M. Thesis, EECS, MIT, May 1998): Three-Dimensional Correspondence.

Sung, K.K. and T. Poggio. "Example-Based Learning for View-Based Human Face Detection," IEEE PAMI, Vol. 20, No. 1, 39-51, 1998.

Todorov, E. and M. Jordan. "Smoothness Maximization along a Predefined Path Accurately Predicts the Speed Profiles of Complex Arm Movements," Journal of Neurophysiology, 80, 696-714, 1998.

Vetter, T. "Synthesis of Novel Views from a Single Face Image," International Journal of Computer Vision, Vol. 28, No. 2, 103-116, 1998.

Weiss, Yair and Edward H. Adelson. Slow and Smooth: A Bayesian Theory for the Combination of Local Motion Signals in Human Vision, CBCL Paper #158/AI Memo 1624, Massachusetts Institute of Technology, Cambridge, MA, February 1998.

Yang, W. and A. Lipman. "VLSI Hardware for Example-based Learning." In: Proceedings of 1998 Image Understanding Workshop, November 1998.

1997:

Anderson, B.L. and P. Sinha. "Reciprocal Interactions between Occlusion and Motion Computations," Proceedings of the National Academy of Sciences, Vol. 94, 3477-3480, 1997.

Avidan, S., T. Evgeniou, A. Shashua and T. Poggio. "Image-Based View Synthesis by Combining Trilinear Tensors and Learning Techniques." In: Proceedings of the ACM Virtual Reality Software Technology Conference (VRST \9297), September 1997.

Avidan, S., T. Evgeniou, A. Shashua and T. Poggio. Image-Based View Synthesis, CBCL Paper #145/AI Memo #1603, Massachusetts Institute of Technology, Cambridge, MA, January 1997.

Bauer, H.U., M. Riesenhuber and T. Geisel. "Calculating Conditions for the Emergence of Structure in Self-Organizing Maps." In: Computation in Neural Systems (CNS*96), Plenum, 247-252, 1997.

Bauer, H.U., M. Riesenhuber, D. Brockmann and T. Geisel. "Analysis of SOM-based Models for the Development of Visual Maps." In: Proceedings of WSOM'97, 233-238, 1997.

Bobick, A., A. Pentland and T. Poggio. "VSAM at the MIT Media Laboratory and CBCL: Learning and Understanding Action in Video Imagery." In: Proceedings of the 1997 Image Understanding Workshop, New Orleans, LA, 25-29, May 1997.

Bricolo, E., T. Poggio, and N. Logothetis. "3D Object Recognition: A Model of View-Tuned Neuron." In: Advances in Neural Information Processing Systems 9, M.I. Jordan, M.C. Mozer and T. Petsche (eds.), M.I.T. Press, Cambridge, MA, 41-47, 1997.

Brooks, R., E. Grimson, T. Poggio, C. Koch, C. Sodini, L. Stein, and W. Yang. "A Trainable Modular Vision System." In: Proceedings of the 1997 Image Understanding Workshop, New Orleans, LA, 1307-1313, 1997.

Brunelli, B. and T. Poggio. "Template Matching: Matched Spatial Filters and Beyond," Pattern Recognition, Vol. 30, No. 5, 751-768, 1997.

Bugeja, A. and W. Yang. "A Coarse-grained, Reconfigurable Image Coprocessor." In: Proceedings of 1997 Image Understanding Workshop, 1391-1397, June 1997.

Bugeja, A. and W. Yang. "A Reconfigurable VLSI Co-processing System for the Block Matching Algorithm." In: IEEE Transactions on VLSI Systems, Vol 5, No 3, 329-337, September 1997.

Cohn, D., Z. Ghahramani and M.I. Jordan. "Active Learning with Statistical Models." In: Multiple Model Approaches to Modeling and Control, Murray-Smith, R., and Johansen, T. A. (Eds.), London: Taylor and Francis, 1997.

Dill, M. and M. Fahle. "Limited Translation Invariance of Human Visual Pattern Recognition," Perception and Psychophysics, 60(1), 65-81, 1997.

Dill, M. and M. Fahle. "The Role of Visual Field Position in Pattern-Discrimination Learning," Proceedings of Royal Society London, B. 264, 1031-1036, 1997.

Dill, M. and S. Edelman. Translation Invariance in Object Recognition, and its Relation to other Visual Transformations, CBCL Paper 150/ AI Memo 1610, Massachusetts Institute of Technology, Cambridge, MA, June 1997.

Edelman, S. and S. Duvdevani-Bar. Visual Recognition and Categorization on the Basis of Similarities to Multiple Class Prototypes, CBCL Paper #154/ AI Memo #1615, Massachusetts Institute of Technology, Cambridge, MA, September 1997.

Evgeniou, T. and T. Poggio. Sparse Representations of Multiple Signals, CBCL Paper #156/ AI Memo #1619, Massachusetts Institute of Technology, Cambridge, MA, September 1997.

Ezzat, T. and T. Poggio. Videorealistic Talking Faces: A Morphing Approach. In: Proceedings of the Audiovisual Speech Production Workshop, Rhodes, Greece, September 1997, in press.

Finn, P., Kavraki, L., Latombe, J.C., Motwani, R., Shelton, C., Venkatasubramanian, S. and Yao, A. RAPID: Randomized Pharmacophore Identification for Drug Design. In: Proceedings of the 13th ACM Symposium on Computational Geometry, Nice, 324-333, 1997.

Geiger, G. and J.Y. Lettvin. A View on Dyslexia, CBCL Paper #148/AI Memo #1608, Massachusetts Institute of Technology, Cambridge, MA, June 1997.

Ghahramani, Z. and M.I. Jordan. "Factorial Hidden Markov Models," Machine Learning, 29, 245-273, 1997.

Ghahramani, Z. and M.I. Jordan. "Mixture Models for Learning from Incomplete Data." In: Computational Learning Theory and Natural Learning Systems, Greiner, R., Petsche, T., and Hanson, S. J. (Eds.), Cambridge, MA: MIT Press, 1997.

Ghahramani, Z., Wolpert, D. M., and M.I. Jordan. "Computational Models of Sensorimotor Organization." In: Self-Organization Computational Maps and Motor Control, P. Morasso and V. Sanguineti (Eds.), Amsterdam: North-Holland, 1997.

Girosi, F. An Equivalence between Sparse Approximation and Support Vector Machines, CBCL Paper #161/AI Memo #1606, Massachusetts Institute of Technology, Cambridge, MA, May 1997.

Grimson, E., P. Viola, O. Faugeras, T. Lorenzo-Perez, T. Poggio, S. Teller. "A Forest of Sensors." In: Proceedings of the 1997 Image Understanding Workshop, New Orleans, LA, 45-50, 1997.

Halperin, D. and Shelton, C.R. "A Perturbation Scheme for Spherical Arrangements with Application to Molecular Modeling." In: Proceedings of the 13th ACM Symposium on Computational Geometry, Nice, 183-192, 1997.

Halperin, D. and Shelton, C.R. A Perturbation Scheme for Spherical Arrangements with Application to Molecular Modeling, AI Laboratory Technical Report #1618, Massachusetts Institute of Technology, Cambridge, MA, 1997.

Jaakkola, T., and M.I. Jordan. "Bayesian Logistic Regression: A Variational Approach." In: Proceedings of the 1997 Conference on Artificial Intelligence and Statistics, D. Madigan and P. Smyth (Eds.), Ft. Lauderdale, FL, 1997.

Jaakkola, T., and M.I. Jordan. "Recursive Algorithms for Approximating Probabilities in Graphical Models." In: Advances in Neural Information Processing Systems 9, M. C. Mozer, M. I. Jordan, and T. Petsche (Eds.), Cambridge MA, MIT Press, 1997.

Jones, M. (Ph.D. Thesis, EECS, MIT, June 1997): "Multidimensional Morphable Models: A Framework for Representing and Matching Object Classes."

Jones, M. and T. Poggio. Model-Based Matching by Linear Combinations of Prototype. In: Proceedings of the 1997 Image Understanding Workshop, New Orleans, LA, 1357-1365, 1997.

Jones, M., P. Sinha, T. Vetter, and T. Poggio. "Top-Down Learning of Low-Level Vision Tasks," Current Biology, Vol. 7, No. 12, 991-994, 1997.

Jordan, M. I. and C. Bishop. "Neural Networks." In: CRC Handbook of Computer Science, Tucker, A. B. (Ed.), Boca Raton, FL, CRC Press, 1997.

Jordan, M. I., Z. Ghahramani and L.K. Saul. "Hidden Markov Decision Trees." In: Advances In: Neural Information Processing Systems 9. M. C. Mozer, M. I. Jordan, and T. Petsche (Eds.), Cambridge MA, MIT Press, 1997.

Li, Zhaoping. Visual Segmentation without Classification in a Model of the Primary Visual Cortex, CBCL Paper #153/AI Memo 1613, Massachusetts Institute of Technology, Cambridge, MA, August 1997.

Lipman, A. and W. Yang. "Hardware for Content-Based Image Queries." In: Proceedings of 1997 Image Understanding Workshop, 1385-1390, June 1997.

Lipman, A. and W. Yang. "VLSI Hardware for Example-Based Learning." In: IEEE Transactions on VLSI Systems, Vol 5, No 3, 320-328, September 1997.

Lipson, P., E. Grimson and P. Sinha. "Configuration-Based Scene Classification and Image Indexing." In: Proceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), Puerto Rico, 1007-1013, 1997.

Meila, M., and M.I. Jordan. "An Objective Function for Belief net Triangulation." In: Proceedings of the 1997 Conference on Artificial Intelligence and Statistics, D. Madigan and P. Smyth (Eds.), Ft. Lauderdale, FL, 1997.

Meila, M., and M.I. Jordan. "Markov Mixtures of Experts." In: Multiple Model Approaches to Modeling and Control, Murray-Smith, R., and Johansen, T. A. (Eds.), London: Taylor and Francis, 1997.

Meila, M., and M.I. Jordan. "Optimal Triangulation with Continuous Cost Functions." In: Advances In: Neural Information Processing Systems 9, M. C. Mozer, M. I. Jordan, and T. Petsche (Eds.), Cambridge MA: MIT Press, 1997.

Meila, Marina and Michael I. Jordan. Triangulation by Continuous Embedding, CBCL Paper #146/AI Memo #1605, Massachusetts Institute of Technology, Cambridge, MA, March 1997.

Meila, Marina, Michael I. Jordan, and Quaid Morris. Estimating Dependency Structure as a Hidden Variable, CBCL Paper #151/AI Memo #1611, Massachusetts Institute of Technology, Cambridge, MA, June 1997.

Mozer, M. C., Jordan, M. I., and Petsche, T. (Eds.). Advances in Neural Information Processing Systems 9, Cambridge MA: MIT Press, 1997.

Mukherjee, S., E. Osuna, and F. Girosi. Nonlinear Prediction of Chaotic Time Series using a Support Vector Machine. In: IEEE Neural Network for Signal Processing (NNSP'97), Amelia Island, FL, September 1997.

Mussa-Ivaldi, F.A. and Bizzi, E. "Learning Newtonian Mechanics." In: Self-Organization, Computational Maps and Motor Control, P. Morasso and V. Sanguineti (Eds.), Elsevier, Amsterdam, 1997, in press.

Oren, M., C. Papageorgiou, P. Sinha, E. Osuna, and T. Poggio. A Trainable System for People Detection. In: Proceedings of the 1997 Image Understanding Workshop, New Orleans, LA, 207-214, May 1997.

Oren, M., C. Papageorgiou, P. Sinha, E. Osuna and T. Poggio. Pedestrian Detection Using Wavelet Templates. In: Proceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), Puerto Rico, 193-199, June 1997.

Osuna, E., R. Freund, and F. Girosi. Improved Training Algorithm for Support Vector Machines. In: IEEE Neural Network for Signal Processing (NNSP'97), Amelia Island, FL, September 1997.

Osuna, E., R. Freund and F. Girosi. Training Support Vector Machines: An Application to Face Detection. In: Proceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), Puerto Rico, 130-136, June 1997.

Osuna, E., R. Freund and F. Girosi. Support Vector Machines: Training and Applications, CBCL Paper #144/AI Memo #1602, Massachusetts Institute of Technology, Cambridge, MA, May 1997.

O'Toole, A.J., T. Vetter, H. Volz and E.M. Salter. "Three-dimensional Caricatures of Human Heads: Distinctiveness and the Perception of Facial Age," Perception, 26, 719-732, 1997.

O'Toole, A.J., T. Vetter, N.F. Toje and H.H. Bülthoff. "Sex Classification is Better with Three-Dimensional Head Structure than with Texture," Perception, 26, 75-84, 1997.

Papageorgiou, C. High Frequency Time Series Analysis and Prediction Using Markov Models. In: Proceedings of Computational Intelligence in Financial Engineering, New York, 182-188, March 1997.

Poggio, T. "Networks that Learn and How the Brain Works." In: Proceedings of Symposia in Pure Mathematics (PSPUM), D. Jerison, I.M. Singer and D.W. Stroock (eds.), American Mathematical Society, Vol. 60, p. 273-312, 1997.

Poggio, T. and P. Sinha. "Image Representations for Graphics and Recognition." In: Proceedings of the IS&T/SPIE Symposium on Electronic Imaging Science and Technology, San Jose, CA, February 1997.

Pontil, P. and A. Verri. Properties of Support Vector Machines, CBCL Paper #152/AI Memo #1612, Massachusetts Institute of Technology, Cambridge, MA, August 1997.

Riesenhuber, M. and P. Dayan. Neural Models for Part-Whole Hierarchies. In: Advances in Neural Information Processing, MIT Press, 9, 17-23, 1997.

Riesenhuber, M. and T. Poggio. "Common Computational Strategies in Machine and Biological Vision." In: Proceedings of International Symposium on System Life, Tokyo, Japan, 67-75, 1997.

Riesenhuber, M., H.U. Bauer and T. Geisel. On-center and Off-center Cell Competition Generates Oriented Receptive Fields from Non-oriented Stimuli in Kohonen's Self-organizing Map. In: Computation in Neural Systems (CNS*96), Plenum, 471-476, 1997.

Sabes, P. and M.I. Jordan. "Obstacle Avoidance and A Perturbation Sensitivity Model for Motor Planning," Journal of Neuroscience, 17, 7119-7128, 1997.

Saul, L. K., and M.I. Jordan. "Mixed Memory Markov Models." In: Proceedings of the 1997 Conference on Artificial Intelligence and Statistics, D. Madigan and P. Smyth (Eds.), Ft. Lauderdale, FL, 1997.

Saul, L. K., and M.I. Jordan. "A Variational Principle for Model-based Interpolation." In: Advances in Neural Information Processing Systems 9. M. C. Mozer, M. I. Jordan, and T. Petsche (Eds.), Cambridge MA: MIT Press, 1997.

Schoelkopf, B., K.K. Sung, C. Burges, F. Girosi, P. Niyogi, T. Poggio and V. Vapnik. Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers, IEEE Transactions on Signal Processing, Vol. 45, No. 11, 2758-2765, 1997.

Sinha, P. and T. Poggio. "Response to 'Comment' article by Lamouret, Cornilleau-Pérès and Droulez," Cognitive Sciences, Vol. 1, No. 2, 43-84, 1997.

Smyth, P., Heckerman, D., and M.I. Jordan. "Probabilistic Independence Networks for Hidden Markov Probability Models," Neural Computation, 9, 227-270, 1997.

Stein, G.P. and A. Shashua. On Degeneracy of linear Reconstruction from Three Views: Linear Line Complex and Applications, CBCL Paper #157/AI Memo #1620, Massachusetts Institute of Technology, Cambridge, MA, December 1997.

Thau, R. (Ph.D. Thesis, EECS, MIT, June 1997): "Reliably Mapping a Robot's Environment Using Fast Vision and Local, but not Global, Metric Data."

Todorov, E., R. Shadmehr and E. Bizzi. "Accelerated Learning of a Difficult Task through Training in a Virtual Environment," J. Motor Behav., 1997, in press.

Vetter, T. "Automated Face Morphing and Image Based Modeling of Faces." In: Proceedings of Imagina'97, INA Monaco, 131-138, 1997.

Vetter, T. "Recognizing Faces from a New Viewpoint." In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP97), Vol. 1, 139-144, 1997.

Vetter, T. and N.F. Troje. "Separation of Texture and Shape in Images of Faces for Image Coding and Synthesis," Journal of the Optical Society of America, 14:9, 2152-2161, 1997.

Vetter, T. and T. Poggio. "Linear Object Classes and Image Synthesis from a Single Example Image." In: Proceedings of IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 19:7, 733-742, 1997.

Vetter, T., M. Jones and T. Poggio. A Bootstrapping Algorithm for Learning Linear Models of Object Classes. In: Proceedings of the 1997 Image Understanding Workshop, New Orleans, LA, May 1997.

Vetter, T., M. Jones and T. Poggio. A Bootstrapping Algorithm for Learning Linear Models of Object Classes. In: Proceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), Puerto Rico, 40-46, 1997.

Vetter, T., M. Jones and T. Poggio. A Bootstrapping Algorithm for Learning Linear Models of Object Classes, CBCL Paper #143/ AI Memo #1600, Massachusetts Institute of Technology, Cambridge, MA, February 1997.

Weiss, Yair. Belief Propagation and Revision in Networks with Loops, CBCL Paper #155/AI Memo #1616, Massachusetts Institute of Technology, Cambridge, MA, November 1997.

1996:

Alpaydin, E., and M.I. Jordan. "Local Linear Perceptrons for Classification," IEEE Transactions on Neural Networks, 7, 788-792, 1996.

Bauer, H.U., M. Riesenhuber and T. Geisel. Phase Diagrams of Self-Organizing Maps, Physical Review E 54, 2807-2810, 1996.

Beymer, D. and T. Poggio. Image Representation for Visual Learning, Science, 272, 1905-1909, 1996.

Beymer, D. and T. Poggio. "Regularization Networks for Visual Learning." In: Early Visual Learning, S. Nayar and T. Poggio (eds.), Oxford University Press, 43-66, 1996.

Beymer, D. and T. Poggio. "Learning to See," IEEE Spectrum, 60-69, May 1996.

Brashers-Krug, T., R. Shadmehr and E. Bizzi. "Consolidation in Human Motor Learning," Nature, 382: 252-255, 1996.

Bricolo, Emanuela (Ph.D. Thesis, BCS, MIT, June 1996): "On the Representation of Novel Objects: Human Psychophysics, Monkey Physiology and Computational Models."

Cohn, D., Z. Ghahramani and M.I. Jordan. "Active Learning with Statistical Models," Journal of Artificial Intelligence Research, 4, 129-145, 1996.

Evgeniou, T. Image Based Rendering Using Algebraic Techniques, CBCL Paper 140/ AI Memo 1592, Massachusetts Institute of Technology, Cambridge, MA, November 1996.

Ezzat, T. and T. Poggio. Facial Analysis and Synthesis Using Image-Based Models. In: Proceedings of the Second International Conference on Automatic Faces and Gesture Recognition, Killington, VT, 116-121, October 1996.

Ezzat, T. and T. Poggio. Facial Analysis and Synthesis Using Image-based Models. In: Proceedings of the Workshop on the Algorithmic Foundations of Robotics, Toulouse, France, 449-467, August 1996.

Gandolfo, F., F.A. Mussa-Ivaldi and E. Bizzi. "Motor Learning by Field Approximation," Proc. of the National Academy of Science, 93: 3843-3846, 1996.

Ghahramani, Z. and M.I. Jordan. "Factorial Hidden Markov Models." In: Advances in Neural Information Processing Systems 8, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1996.

Ghahramani, Z., D. Wolpert and M.I. Jordan. "Generalization to Local Remappings of the Visuomotor Coordinate Transformation," Journal of Neuroscience, 16, 7085-7096, 1996.

Ghahramani, Zoubin and Michael I. Jordan. Factorial Hidden Markov Models, CBCL Paper #130/AI Memo #1561, Massachusetts Institute of Technology, Cambridge, MA, January 1996.

Grimson, W.E.L., B.K.P. Horn, T. Poggio and the staff of the AI Laboratory. "Progress in Image Understanding at MIT." In: Proceedings of the 1996 Image Understanding Workshop, Morgan Kaufmann, San Francisco, CA, 65-74, 1996.

Jaakkola, T., and M.I. Jordan. "Computing Upper and Lower Bounds on Likelihoods on Intractable Networks." In: Workshop on Uncertainty in Artificial Intelligence, E. Horvitz (Ed.), Portland, Oregon, 1996.

Jaakkola, T., L.K. Saul, and M.I. Jordan. "Fast Learning by Bounding Likelihoods in Sigmoid Belief Networks." In: Advances in Neural Information Processing Systems 8, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA, MIT Press, 1996.

Jaakkola, Tommi S. and Michael I. Jordan. Computing Upper and Lower Bounds on Likelihoods in Intractable Networks, CBCL Paper #136/AI Memo #1571, Massachusetts Institute of Technology, Cambridge, MA, March 1996.

Jaakkola, Tommi S., Lawrence K. Saul, Michael I. Jordan. Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks, CBCL Paper #129/AI Memo #1560, Massachusetts Institute of Technology, Cambridge, MA, January 1996.

Jones, M. and T. Poggio. Model-based Matching by Linear Combinations of Prototypes, CBCL Paper #139/AI Memo #1583, Massachusetts Institute of Technology, Cambridge, MA, September 1996.

Jordan, M. I. "Computational Aspects of Motor Control and Motor Learning." In: Handbook of Perception and Action Motor Skills, H. Heuer and S. Keele (Eds.), New York, NY, Academic Press, 1996.

Jordan, M. I. and C. Bishop. "Neural Networks,"Computing Surveys, 28, 73-75, 1996.

Jordan, Michael I. and Christopher M. Bishop. Neural Networks, CBCL Paper #131/AI Memo #1562, Massachusetts Institute of Technology, Cambridge, MA, March 1996.

Lemm, J.D. Prior Information and Generalized Questions, CBCL Paper #141/AI Memo #1598, Massachusetts Institute of Technology, Cambridge, MA, December 1996.

Lines, Stephen (S.M. Thesis, EECS, MIT, June 1996): "The Photo-Realistic Synthesis of Novel Views from Example Images."

Martinez, D. and W. Yang. "Competitive Leaning Algorithms for Channel Optimized Vector Quantizers." In: The 1996 IEEE International Conference on Neural Networks, 1462-1467, June 1996.

McIntyre, J., F.A. Mussa-Ivaldi and E. Bizzi. "The Control of Stable Postures in the Multi-joint Arm," Exp. Brain Res., Brain Res., 110: 248-264, 1996.

Meila, M. and M.I. Jordan. "Learning Fine Motion by Markov Mixtures of Experts." In: Advances in Neural Information Processing Systems 8, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1996.

Nayar, S. and T. Poggio. "Learning and Vision." In: Early Visual Learning, S. Nayar and T. Poggio (eds.), Oxford University Press, 1-8, 1996.

Niyogi, P. and F. Girosi. On The Relationship between Generalization Error, Hypothesis Complexity and Sample Complexity for Radial Basis Functions, Neural Computation, 8, 819-842, 1996.

Olshausen, Bruno A. Learning Linear, Sparse, Factorial Codes, CBCL Paper #138/AI Memo #1580, Massachusetts Institute of Technology, Cambridge, MA, July 1996.

Pauls, J., E. Bricolo and N. Logothetis. "View Invariant Representations in Monkey Temporal Cortex: Position, Scale and Rotational Invariance." In: Early Visual Learning, S. Nayar and T. Poggio (eds.), Oxford University Press, 9-42, 1996.

Poggio, T. "Networks that Learn and How the Brain Works." In: Proceedings of Symposia in Pure Mathematics (PSPUM), D. Jerison, I.M. Singer and D.W. Stroock (eds.), American Mathematical Society, 1996.

Poggio, T. and K.K. Sung. Networks that Learn for Image Understanding. In: Advances in Image Understanding, K. Bowyer and N. Ahuja (eds.), IEEE Computer Society Press, 226-240, 1996.

Riesenhuber, M., H.U. Bauer and T. Geisel. Analyzing the Formation of Structure in High-dimensional Self-organizing Maps Reveals Differences to Feature Map Models. In: Artificial Neural Networks - ICANN'96, Vol. 1112 of Lecture Notes in Computer Science, Springer, 409-411, 1996.

Riesenhuber, M., H.U. Bauer and T. Geisel. Analyzing Phase Transitions in High-Dimensional Self-Organizing Maps, Biological Cybernetics 75, 397-407, 1996.

Romano, R., D. Beymer and T. Poggio. "Face Verification for Real-time Applications." In: Proceedings of the 1996 Image Understanding Workshop, Morgan Kaufmann, San Francisco, CA, 1996.

Sabes, P. and M.I. Jordan. "Reinforcement Learning by Probability Matching." In: Advances in Neural Information Processing Systems 8, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1996.

Sabes, Philip N. and Michael I. Jordan. Reinforcement Learning by Probability Matching, CBCL Paper #134/AI Memo #1568, Massachusetts Institute of Technology, Cambridge, MA, January 1996.

Saul, L.K. and M.I. Jordan. "Exploiting Tractable Substructures in Intractable Networks." In: Advances in Neural Information Processing Systems 8, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1996.

Saul, L.K., T. Jaakkola and M.I. Jordan. "Mean Field Theory for Sigmoid Belief Networks," Journal of Artificial Intelligence Research, 4, 61-76, 1996.

Saul, Lawrence K., Tommi Jaakkola and Michael I. Jordan. Mean Field Theory for Sigmoid Belief Networks, CBCL Paper #135/AI Memo #1570, Massachusetts Institute of Technology, Cambridge, MA, March 1996.

Schoelkopf, B., K. Sung, C. Burges, F. Girosi, P. Niyogi, T. Poggio and V. Vapnik. Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers, CBCL Paper 142/AI Memo 1599, Massachusetts Institute of Technology, Cambridge, MA, December 1996.

Sinha, P. "The Coherence of Subjective Gratings," Vision Research, 36(22), 3661-3665, 1996.

Sinha, P. and T. Poggio. "I think I Know that Face...," Nature (Correspondence), Vol. 384, No. 6608, 404, 1996.

Sinha, P. and T. Poggio. "Role of Learning in Three-dimensional Form Perception," Nature, Vol. 384, No. 6608, 460-463, 1996.

Smyth, Padhraic, David Heckerman and Michael Jordan. Probabilistic Independence Networks for Hidden Markov Probability Models, CBCL Paper #132/AI Memo #1565, Massachusetts Institute of Technology, Cambridge, MA, February 1996.

Sung, Kah-Kay (Ph.D. Thesis, EECS, MIT, February 1996): "Learning and Example Selection for Object and Pattern Detection."

Xu, L. and M.I. Jordan. "On Convergence Properties of the EM Algorithm for Gaussian Mixtures," Neural Computation , 8, 129-151, 1996.

Yiu, Elaine (S.M. Thesis, EECS, MIT, June 1996): "Image Classification Using Color Cues and Texture Orientation."

1995:

Ancona, N. and T. Poggio. Optical Flow from 1-D Correlation: Application to a Simple Time-to-Crash Detector, International Journal of Computer Vision, Vol. 14, 131-146, 1995.

Beymer, D. (Ph.D. Thesis, EECS, MIT, August 1995): "Pose-invariant Face Recognition Using Real and Virtual Views."

Beymer, D. Vectorizing Face Images by Interleaving Shape and Texture Computations, CBCL Paper #122/AI Memo #1537, Massachusetts Institute of Technology, Cambridge, MA, September 1995.

Beymer, D. and T. Poggio. "Face Recognition from One Example View." In: Proceedings of the IEEE 5th International Conference on Computer Vision, IEEE Computer Society Press, Cambridge, MA, 500-507, June 1995.

Beymer, D. and T. Poggio. Face Recognition from One Example View, CBCL Paper #121/AI Memo #1536, Massachusetts Institute of Technology, Cambridge, MA, September 1995.

Bizzi, E., S.F. Giszter, E. Loeb, F.A. Mussa-Ivaldi and P. Saltiel. "Modular Organization of Motor Behavior in the Frog's Spinal Cord," Trends in NeuroSci., 18: 442-445, 1995.

Brunelli, R. and T. Poggio. Template Matching: Matched Spatial Filters and Beyond, CBCL Paper 123/AI Memo 1549, Massachusetts Institute of Technology, Cambridge, MA, October 1995.

Brunelli, R., D. Falavigna, T. Poggio and L. Stringa. "Automatic Person Recognition by Acoustic and Geometric Features," Machine Vision and Applications, Vol. 8, 317-325, 1995.

Chan, N. (S.M. Thesis, EECS, MIT, May 1995): "The Complexity and A Priori Knowledge of Learning From Examples."

Cohn, D., Z. Ghahramani and M.I. Jordan. "Active Learning with Statistical Models." In: Advances in Neural Information Processing Systems 7, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1995.

Cohn, David A. Minimizing Statistical Bias with Queries, CBCL Paper #124/AI Memo #1552, Massachusetts Institute of Technology, Cambridge, MA, September 1995.

Fahle, M., S. Edelman, and T. Poggio. "Fast Perceptual Learning in Visual Hyperacuity," Vision Research, Vol. 35, 21, 3003-3013, 1995.

Fun, W., and M.I. Jordan. "The Moving Basin: Effective Action-Search in Adaptive Control." In: Proceedings of the World Conference on Neural Networks, Washington, DC., 1995.

Ghahramani, Z., Wolpert, D. M., and M.I. Jordan. "Computational Structure of Coordinate Transformations: A Generalization Study. In: Advances in Neural Information Processing Systems 7, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1995.

Girosi, F. Approximation Error Bounds that Use VC-bounds. In: Proceedings of the International Conference on Artificial Neural Networks, 295-302, Paris, October 9-13, 1995.

Girosi, F. and N. Chan. Prior Knowledge and the Creation of Virtual Examples for RBF Networks. In: Neural Networks Signal Processing Proceedings of the 1995/IEEE-SP/Workshop, IEEE Signal Processing Society, Cambridge, MA, 201-210, September 1995.

Girosi, F., M. Jones, and T. Poggio. Regularization Theory and Neural Networks Architectures, Neural Computation, Vol. 7, No. 2, 219-269, 1995.

Jaakkola, T., Singh, S. P., and M.I. Jordan. Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems." In: Advances in Neural Information Processing Systems 7, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA, MIT Press, 1995.

Jones, M. and T. Poggio. Model-based Matching of Line Drawings by Linear Combinations of Prototypes. In: Proceedings of the IEEE 5th International Conference on Computer Vision, IEEE Computer Society Press, Cambridge, MA, 531-536, June 1995.

Jones, M. and T. Poggio. Model-based Matching of Line Drawings by Linear Combinations of Prototypes, CBCL Paper #128/AI Memo #1559, Massachusetts Institute of Technology, Cambridge, MA, December 1995.

Jordan, M. I. "The Organization of Action Sequences: Evidence from a Relearning Task," Journal of Motor Behavior, 27, 179-192, 1995.

Jordan, M.I. and R.A. Jacobs. "Reinforcement Learning with Soft State Aggregation." In: Advances in Neural Information Processing Systems 7, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA, MIT Press, 1995.

Jordan, M. I. and L. Xu. "Convergence Results for the EM Approach to Mixtures-of-Experts Architectures," Neural Networks, 8, 1409-1431, 1995.

Leopold, D. A., J. C. Fitzgibbons, and N. K. Logothetis. The Role of Attention in Binocular Rivalry as Revealed through Optokinetic Nystagmus, CBCL Paper #126/AI Memo #1554, Massachusetts Institute of Technology, Cambridge, MA, November 1995.

Logothetis, N. K. and D. A. Leopold. On the Physiology of Bistable Percepts, CBCL Paper #125/AI Memo #1553, Massachusetts Institute of Technology, Cambridge, MA, November 1995.

Logothetis, N.K, J. Pauls, and T. Poggio. "Shape Representation in the Inferior Temporal Cortex of Monkeys," Current Biology, Vol. 5, No. 5, 552-563, 1995.

Martinez, D. and W. Yang. "A Robust Backward Adaptive Quantizer." In: Proceedings of IEEE Workshop on Neural Networks for Signal Processing V, 531-540, August 1995.

Niyogi, P. (Ph.D. Thesis, EECS, MIT, February 1995): "The Informational Complexity of Learning from Examples."

Poggio, T. and D. Beymer. "Learning Networks for Face Analysis and Synthesis." In: Proceedings of the International Workshop on Automatic Face- and Gesture-recognition, Martin Bichsel (ed.), Zurich, Switzerland, 160-165, 1995.

Riesenhuber, M., H.U. Bauer and T. Geisel. Beyond Feature Map Models: Analyzing the Emergence of Ocular Dominance and Orientation Columns in High-dimensional Self-organizing Maps. In: Learning and Memory: Proceedings of the 23^rd Göttingen Neurobiology Conference 1995, Georg Thieme Verlang, Stuttgart, Vol. 1, 1995.

Saul, L. K., and M.I. Jordan. "Boltzmann Chains and Hidden Markov Models." In: Advances in Neural Information Processing Systems 7, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1995.

Singh, S. P., T. Jaakkola, M.I. Jordan and R.A. Jacobs. "Learning in Modular and Hierarchical Systems." In: The Handbook of Brain Theory and Neural Networks, M. Arbib (Ed.), Cambridge, MA, MIT Press, 1995.

Sinha, P. (Ph.D. Thesis, EECS, MIT, August 1995): "Perceiving and Recognizing Three-Dimensional Forms."

Somers, David C., Emanuel V. Todorov, Athanassios G. Siapas and Mgriganka Sur. Vector-Space Integration of Local and Long-Range Information in Visual Cortex, CBCL Paper #127/AI Memo #1556, Massachusetts Institute of Technology, Cambridge, MA, November 1995.

Sung, K.K. and T. Poggio. Finding Human Faces with a Gaussian Mixture Distribution-based Face Model, Recent Progress in Computer Vision, LNCS Series, Springer-Verlag, 1995.

Sung, K.K. and T. Poggio. Finding Human Faces with a Gaussian Mixture Distribution-based Face Model. In: Proceedings of Second Asian Conference on Computer Vision, Singapore, December 1995.

Vetter, T., A. Hurlbert, and T. Poggio. "View-based Models of 3D Object Recognition: Invariance to Imaging Transformations," Cerebral Cortex, Vol. 5, No. 3, 261-269, 1995.

Wolpert, D., Z. Ghahramani and M.I. Jordan. "Are Arm Trajectories Planned in Kinematic or Dynamic Coordinates? An Adaptation Study," Experimental Brain Research, 103, 460-470, 1995.

Wolpert, D., Z. Ghahramani and M.I. Jordan. "An Internal forward Model for Sensorimotor Integration," Science, 269, 1880-1882, 1995.

Wolpert, D. M., Ghahramani, Z., and M.I. Jordan. "Neural forward Dynamic Models in Human Motor Control: Psychophysical Evidence." In: Advances in Neural Information Processing Systems 7, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1995.

Xu, L., Jordan, M. I., and Hinton, G. E. "An Alternative Model for Mixtures of Experts." In: Advances in Neural Information Processing Systems 7, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (Eds.), Cambridge MA: MIT Press, 1995.

1994

Vetter, T. and T. Poggio.\A0Symmetric 3D Objects are an Easy Case for 2D Object Recognition, Spatial Vision, 8, No. 4, 443-453, 1994.

Poggio, T.\A0 L\92Intelligenza e Saper Imparare, Sistemi & Impresa, No. 4, 19-22, 1994.

Logothetis, N.K., J. Pauls, H. B\FClthoff and T. Poggio. View-dependent Object Recognition by Monkeys, Current Biology, 4, No. 5, 401-414, 1994.

Hutchinson, J.M., A. Lo and T. Poggio.A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks, Journal of Finance, Vol. XLIX, No. 3, 851-889, 1994.

Vetter, T., T. Poggio and H. B\FClthoff.The Importance of Symmetry and Virtual Views in Three-dimensional Object Recognition, Current Biology, 4, No. 1, 18-23, 1994.

1993

Poggio, T.\A0 In Memorium: Werner Reichardt, 1924-1992, Biological Cybernetics, 69, 1, 1-3, 1993.

Brunelli, R. and T. Poggio.\A0Caricatural Effects in Automated Face Perception, Biological Cybernetics, 69, 235-241, 1993.

Brunelli, R. and T. Poggio. Face Recognition: Features Versus Templates, IEEE PAMI, 15, 1042-1052, 1993.

1992

Poggio, T., S. Edelman and M. Fahle. Learning of Visual Modules from Examples: A Framework for Understanding Adaptive Visual Performance, Computer Vision, Graphics and Image Processing B: Image Understanding, 56, No. 1, 22-30,1992.

Wyatt, J.L., C. Keast, M. Seidel, D. Standley, B. Horn, T. Knight, C. Sodini, H.-S. Lee and T. Poggio).\A0Analog VLSI Systems for Image Acquisition and Fast Early Vision Processing, International Journal of Computer Vision, 8, No. 3, 217-230, 1992.

Poggio, T. and L. Stringa.\A0A Project for an Intelligent System: Vision and Learning, International Journal of Quantum Chemistry, 42, 727-739, 1992.

Poggio, T., M. Fahle and S. Edelman. Fast Perceptual Learning in Visual Hyperacuity, Science, 256, 1018-1021, May 1992.

Edelman, S. and T. Poggio.\A0Bringing the Grandmother Back into the Picture: A Memory-based View of Object Recognition, International Journal of Pattern Recognition of Artificial Intelligence, 6, 37-61, April, 1992.

1991

Edelman, S. and T. Poggio.\A0Models of Object Recognition, Current Opinion in Neurobiology, 1, 270-273, 1991.

Weems, C., C. Brown, J. Webb, and J. Kender. Parallel Processing in the DARPA Strategic Computing Vision Program, IEEE Expert, 6, 23-38, October 1991.

1990

Poggio, T. and F. Girosi.\A0Networks for Approximation and Learning, Proceedings of theIEEE (special issue: Neural Networks I: Theory and Modeling), Vol. 78, No. 9, 1481-1497, September 1990.

Kanade, K., T. Binford, T. Poggio and A. Rosenfeld.Vision, Annual Review of Computer Science 4, 517-529, 1990.

Girosi, F. and T. Poggio.\A0 Networks and the Best Approximation Property, Biological Cybernetics, 63, 3, 169-176, 1990.

Edelman, S. and T. Poggio.\A0A Network that Learns to Recognize 3D Objects, Nature, 343, 263-266, 1990.

Poggio, T. and F. Girosi.\A0Regularization Algorithms for Learning that are Equivalent to Multilayer Networks, Science, 247, 978-982, 1990.

1989

Poggio, T.\A0 Visione Biologica and Visione Artifiale, SFERA, 6, 164-5, 1989.

Girosi, F. and T. Poggio. Representation Properties of Networks: Kolmogorov\92s Theorem is Irrelevant, Neural Computation, 1, 465-469, 1989.

Poggio, T.\A0 Oltre l\92Immagine\94 or \93Beyond the Image, Ulisse 2000, 63, 76-86, June 1989.

Edelman, S. and T. Poggio.\A0Integrating Visual Cues for Object Segmentation and Recognition, Optics News, 15, 8-16, 1989.

Gamble, E., D. Geiger, T. Poggio and D. Weinshall.\A0 Integration of Vision Modules and Labelling of Surface Discontinuities, IEEE Trans. Systems, Man & Cybernetics, 19, 6, 1576-1581, 1989.

B\FClthoff, H.H., J. Little and T. Poggio.A Parallel Algorithm for Real Time Computation of Optical Flow, Nature, 337, 549-553, 1989.

Hurlbert, A. and T. Poggio.\A0Rendere le Macchine (e l\92Intelligenza Artificiale) in Grado di Vedere, Sistemi Intelligenti, 1, 75-103, 1989.

Verri, A. and T. Poggio.\A0 Motion Field and Optical Flow: Qualitative Properties, IEEE Trans. PAMI, 11, 490-498, 1989.

1988

Bertero, M., T. Poggio and V. Torre. Ill-posed Problems in Early Vision, Proceedings of the IEEE, 76, 869-889, 1988.

Little, J., T. Poggio, and E.B. Gamble. Seeing in Parallel: The Vision Machine, International Journal of Supercomputer Applications, 2, 4, 13-28, 1988.

Poggio, T., E. Gamble and J. Little. Parallel Integration of Vision Modules, Science, 242, 436-440, 1988.

Voorhees, H. and T. Poggio.\A0 Computing Texture Boundaries from Images, Nature, 333, 364-367, 1988.

Poggio, T., H. Voorhees and A. Yuille. A Regularized Solution to Edge Detection, Journal of Complexity, 4, 106-123, 1988.

Hurlbert, A. and T. Poggio.\A0 Synthesizing a Color Algorithm from Examples, Science, 239, 482-485, 1988.

1987

Poggio, T. and C. Koch.\A0 Synapses that Compute Motion, Scientific American, 256, 46-52, 1987.

Marroquin, J., S. Mitter and T. Poggio. Probabilistic Solution of Ill-posed Problems in Computational Vision, Journal of American Statistical Association, 82, 76-89, 1987

1986

Hurlbert, A. and T. Poggio.\A0 Do Computers Need Attention?, Nature, 321, 651-652, 1986.

Koch, C., V. Torre and T. Poggio. Computations in the Vertebrate Retina: Gain Enhancement, Differentiation and Motion Discrimination, Trends in Neurosciences, 9, 204-211, 1986.

Yuille, A.L. and T. Poggio.\A0 Scaling Theorems for Zero Crossings, IEEE Trans. PAMI, 8, 15-25, 1986.

Torre, V. and T. Poggio.\A0 On Edge Detection, IEEE Trans. PAMI, 8, 147-163, 1986.

1985

Poggio, T. and C. Koch.\A0 Ill-posed Problems in Early Vision: From Computational Theory to Analog Networks, Proceedings of the Royal Society London B, 226, 303-323, 1985.

Hurlbert, A. and T. Poggio.\A0 Spotlight on Attention, Trends in Neurosciences, 8, 309-311, 1985.

Poggio, T., V. Torre and C. Koch. Computational Vision and Regularization Theory, Nature, 317, 314-319, 1985.

Poggio, T.\A0 Early Vision: From Computational Structure to Algorithms and Parallel Hardware, Computer Vision, Graphics, and Image Processing, 31, 139-155, 1985.

Koch, C. and T. Poggio.\A0 The Biophysical Properties of Spines as a Basis for their Electrical Function: A Comment on Kawato and Tsukahara, 1983, Journal of Theoretical Biology, 113, 225-229, 1985.

Koch, C. and T. Poggio. A Simple Algorithm for Solving the Cable Equation in Dendritic Trees of Arbitrary Geometry, J. Neuroscience Methods, 12, 303-315, 1985.

Yuille, A. and T. Poggio.\A0 Fingerprints Theorems for Zero Crossing, J. Optical Society America A, 2, 683-692, 1985.

1984

Nielsen, K.R.K. and T. Poggio. Vertical Image Registration in Stereopsis, Vision Research, 24, 1133-1140, 1984.

Poggio, T.\A0 Vision by Man and Machine, Scientific American, 250, 106-116, 1984.

Poggio, G. and T. Poggio.\A0 The Analysis of Stereopsis, Annual Review of Neuroscience, 7, 379-412, 1984.

1983

Koch, C. and T. Poggio.\A0 A Theoretical Analysis of Electrical Properties of Spines, Proceedings of the Royal Society London B, 218, 455-477, 1983.

Koch, C., T. Poggio and V. Torre. Nonlinear Interactions in a Dendritic Tree: Localization, Timing and Role in Information Processing, PNAS, 80, 2799-2802, 1983.

Reichardt, W., T. Poggio and K. Hausen. Figure-ground Discrimination by Relative Movement in the Visual System of the Fly - II: Towards the Neural Circuitry, Biological Cybernetics, 46, 1-30, 1983.

Koch, C. and T. Poggio.\A0 Electrical Properties of Dendritic Spines, Trends in Neurosciences, 6, 80-83, 1983.

1982

Nishihara, H.K. and T. Poggio. Hidden Cues in Random-line Stereograms, Nature, 300, 347-349, 1982.

Wehrhahn, C., T. Poggio and T. B\FClthoff. Tracking and Chasing in Houseflies (Musca): An Analysis of 3D Flight Trajectories, Biological Cybernetics, 45, 123-130, 1982.

Koch, C., T. Poggio and V. Torre. Retinal Ganglion Cells: A Functional Interpretation of Dendritic Morphology, Proceedings of the Royal Society London, 298, 227-264, 1982.

1981

Fahle, M. and T. Poggio.\A0 Visual Hyperacuity: Spatiotemporal Interpolation in Human Vision, Proceedings of the Royal Society London B, 213, 451-477, 1981.

Poggio, T.\A0 Marr\92s Computational Approach to Vision, Trends in Neurosciences, 10, 258-262, 1981.

Poggio, T., W. Reichardt and W. Hausen. A Neuronal Circuitry for Relative Movement Discrimination by the Visual System of the Fly, Naturwissenschaften, 68, 9, 443-466, 1981.

Poggio, T. and W. Reichardt.\A0 Visual Fixation and Tracking by Flies: Mathematical Properties of Simple Control Systems, Biological Cybernetics, 40, 101-112, 1981.

Geiger, G. and T. Poggio.\A0 Asymptotic Oscillations in the Tracking Behavior of the Fly Musca Domestica, Biological Cybernetics, 41, 197-201, 1981.