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• 2012 (8)
• 2011 (16)
• 2010 (18)
• 2009 (16)
• 2008 (18)
• 2007 (20)
• 2006 (13)

List of Publications

• Chikkerur S., Serre T., Poggio T., A Bayesian inference theory of attention: neuroscience and algorithms , CSAIL Technical Report, MIT-CSAIL-TR-2009-047/CBCL-280, 2009 Download
• Jhuang H., Serre T., Wolf L., Poggio T., A Biologically Inspired System for Action Recognition , ICCV 2007, , 2007 Download
• Kouh M., Poggio T., A Canonical Neural Circuit for Cortical Nonlinear Operations , NECO, Vol. 20, No. 6, Pages 1427-1451, 2008 Download
• Heisele B., Serre T., Poggio T., A Component-based Framework for Face Detection and Identification , IJCV , 74(2), pp. 167-181, 2007 Download
• Yokoyama M., Poggio T., A Contour-Based Moving Object Detection , IEEJ Trans. Electron. Inf. Syst., Volume 129, Issue 5, pp. 812-817 [DOI: 10.1541/ieejeiss.129.812], 2009 Download
• Caponnetto A., Yao Y., Adaptation for Regularization Operators in Learning Theory , CSAIL Technical Report, MIT-CSAIL-TR-2006-063 CBCL-265, 2006 Download
• De Vito E., Pereverzyev S., Rosasco L., Adaptive Kernel Methods Using the Balancing Principle , Foundations of Computational Mathematics, Volume 10, Number 4, 455-479, [doi: 10.1007/s10208-010-9064-2], 2010 Download
• De Vito E., Pereverzyev S., Rosasco L., Adaptive Kernel Methods Using the Balancing Principle , CSAIL Technical Report, MIT-CSAIL-TR-2008-062/ CBCL-275, 2008 Download
• Serre T., Oliva A., Poggio T., A Feedforward Architecture Accounts for Rapid Categorization , PNAS 2007, Vol. 104, No. 15, 6424-6429, 2007 Download
• Isik L., Leibo J., Mutch J., Lee S., Poggio T., J.Z. Leibo, J. Mutch, S.W. Lee, T Poggio. A hierarchical model of peripheral vision , CSAIL Technical Report, MIT-CSAIL-TR-2011-031/CBCL-300, 2011 Download
• Rosasco L., Barla A., Mosci S., Verri A., A method for robust variable selection with significance assessments , ESANN 2008 Proc., , 2008 Download
• Ezzat T., Bouvrie J., Poggio T., AM-FM Demodulation of Spectrograms using 2-D Max-Gabor Analysis , ICASSP2007, , 2007 Download
• Cadieu C., Kouh M., Pasupathy A., Connor C., Riesenhuber M., Poggio T., A Model of V4 Shape Selectivity and Invariance , J. Neurophysiol. , Vol. 98, 1733-1750, 2007 Download
• Bileschi S., A Multi-Scale Generalization of the HoG and HMAX Image Descriptors for Object Detection , CSAIL Technical Report, MIT-CSAIL-TR-2008-019/CBCL-271, 2008 Download
• Serre T., Poggio T., A Neuromorphic Approach to Computer Vision , Communications of the ACM (online), Vol . 53, No. 10 [doi :10.1145/1831407.1831425], 2010 Download
• Bouvrie J., Ezzat T., An Incremental Algorithm for Signal Reconstruction from Short-time Fourier Transform Magnitude. , ICSLP 2006, , 2006 Download
• Chikkerur S., Tan C., Serre T., Poggio T., An integrated model of visual attention using shape-based features , CSAIL Technical Report, MIT-CSAIL-TR-2009-029/CBCL-278, 2009 Download
• Rosasco L., Belkin M., De Vito E., A Note on Perturbation Results for Learning Empirical Operators , CSAIL Technical Report, MIT-CSAIL-TR-2008-052/CBCL-274, 2008 Download
• Chikkerur S., Poggio T., Approximations in the HMAX Model , CSAIL Technical Report, MIT-CSAIL-TR-2011-021/CBCL-298, 2011 Download
• Rosasco L., Mosci S., Villa A., Verri A., A primal-dual algorithm for group sparse regularization with overlapping groups , NIPS 2010, , 2010 Download
• Serre T., Kreiman G., Kouh M., Cadieu C., Knoblich U., Poggio T., Vol. 165, 33-56 A quantitative theory of immediate visual recognition , Prog. Brain Res., , 2007 Download
• Chikkerur S., Serre T., Poggio T., Attentive processing improves object recognition , CSAIL Technical Report, MIT-CSAIL-TR-2009-046 /CBCL-279, 2009 Download
• Bileschi S., Wolf L., A Unified System for Object Detection, Texture Recognition and Context Analysis Based on the Standard Model Feature Set , BMVC 2006, , 2006 Download
• Yu X., Steele A., Khilnani V., Garrote Contreras E., Jhuang H., Serre T., Poggio T., , Automated home-cage behavioral phenotyping of mice , CSAIL Technical Report, MIT-CSAIL-TR-2009-052 CBCL-283, 2009 Download
• Jhuang H., Garrote Contreras E., Mutch J., Yu X., Khilnani V., Poggio T., Steele A., Serre T., Automated home-cage behavioural phenotyping of mice , Nature Communications, 1, Article 68, [doi: 10.1038/ncomms1064], 2010 Download
• Knoblich U., Bouvrie J., Poggio T., Biophysical Models of Neural Computation: Max and Tuning Circuits , CSAIL Technical Report, CBCL Paper, 2007 Download
• Knoblich U., Bouvrie J., Poggio T., Biophysical Models of Neural Computation: Max and Tuning Circuits , WImBI 2006, , 2006 Download
• Mutch J., Knoblich U., Poggio T., CNS: a GPU-based framework for simulating cortically-organized networks , CSAIL Technical Report, MIT-CSAIL-TR-2010-013 / CBCL-286, 2010 Download
• Smale S., Poggio T., Caponnetto A., Bouvrie J., Derived Distance: towards a mathematical theory of visual cortex , CSAIL Technical Report, CBCL Paper, 2007 Download
• Ezzat T., Poggio T., Discriminative Word-Spotting Using Ordered Spectro-Temporal Patch Features , SAPA 2008, , 2008
• Jhuang H., Dorsal Stream: From Algorithm to Neuroscience , MIT EECS, , 2011 Download
• Cardin J., Carlén M., Meletis K., Knoblich U., Zhang F., Deisseroth K., Tsai L., Moore C., , Driving fast-spiking cells induces gamma rhythm and controls sensory responses. , Nature, 459(7247):663-667 [doi: 10.1038/nature08002], 2009 Download
• Meyers E., Freedman D., Kreiman G., Miller E., Poggio T., Dynamic Population Coding of Category Information in Inferior Temporal and Prefrontal Cortex , J. Neurophysiol. , Vol. 100, no. 3: 1407-1419, 2008 Download
• De Mol C., De Vito E., Rosasco L., Elastic-Net Regularization in Learning Theory , JComp, Vol. 25, Issue 2, Pages 201–230, 2009 Download
• De Mol C., De Vito E., Rosasco L., Elastic-Net Regularization in Learning Theory , CSAIL Technical Report, MIT-CSAIL-TR-2008-046/CBCL-273, 2008 Download
• Chikkerur S., Wolf L., Empirical Comparison between Hierarchical Fragments Based and Standard Model Based Object Recognition Systems , CSAIL Technical Report, CBCL Paper #MMVI-0I, 2006 Download
• Meyers E., Embark H., Freiwald W., Serre T., Kreiman G., Poggio T., Examining high level neural representations of cluttered scenes , CSAIL Technical Report, MIT-CSAIL-TR-2010-034 / CBCL-289, 2010 Download
• Freedman D., Riesenhuber M., Poggio T., Miller E., Experience dependent sharpening of visual shape selectivity in inferior temporal cortex , Cerebral Cortex, 16: 1631-1644, 2006 Download
• Rosasco L., Mosci, S.; A. Barla; A. Verri Finding Structured Gene Signatures , Proc. of IEEE BIBM, 2008, , 2008
• Leibo J., Mutch J., Ullman S., Poggio T., From primal templates to invariant recognition , CSAIL Technical Report, MIT-CSAIL-TR-2010-057/CBCL-293, 2010 Download
• Bileschi S., Fully automatic calibration of LIDAR and video streams from a vehicle , ICCV 2009, 1457 - 1464 [doi:10.1109/ICCVW.2009.5457439], 2009 Download
• Bouvrie J., Poggio T., Rosasco L., Smale S., Wibisono A., Generalization and Properties of the Neural Response , CSAIL Technical Report, MIT-CSAIL-TR-2010-051/CBCL-292, 2010 Download
• Tacchetti A., Mallapragada P., Santoro M., Rosasco L., GURLS: a Toolbox for Regularized Least Squares Learning , CSAIL Technical Report, MIT-CSAIL-TR-2012-003/CBCL-306, 2012 Download
• Kuehne T., Jhuang H., Garrote Contreras E., Poggio T., Serre T., HMDB: A Large Video Database for Human Motion Recognition , ICCV 2011, , 2011 Download
• Leibo J., Mutch J., Poggio T., How can cells in the anterior medial face patch be viewpoint invariant? , COSYNE 2011, , 2011 Download
• Poggio T., Editors: G. Jacovitt, A. Pettorossi, R. Consolo and V. Senni How the Brain Might Work: The Role of Information and Learning in Understanding and Replicating Intelligence , Information: Science and Technology for the New Century, pp. 45-61, 2007 Download
• Bileschi S., Wolf L., Image representations beyond histograms of gradients: The role of Gestalt descriptors , CVPR '07, Pages 1-8, 2007 Download
• Meyers E., Qi X., Constantinidis C., Incorporation of new information into prefrontal cortical activity after learning working memory tasks , PNAS 2012, vol. 109 no. 12 4651-4656 ( ), 2012 Download
• Rosasco L., Mosci S., Santoro M., Verri A., Villa S., Iterative Projection Methods for Structured Sparsity Regularization , CSAIL Technical Report, MIT-CSAIL-TR-2009-50 / CBCL-282, 2009 Download
• Alvarez M., Rosasco L., Lawrence N., Kernels for Vector-Valued Functions: a Review , CSAIL Technical Report, MIT-CSAIL-TR-2011-033/CBCL-301, 2011 Download
• Isik L., Leibo J., Poggio T., MIT-CSAIL-TR-2011-040/CBCL-302 Learning and disrupting invariance in visual recognition , CSAIL Technical Report, , 2011 Download
• Isik L., Leibo J., Poggio T., Learning and disrupting invariance in visual recognition with a temporal association rule , Front. Comput. Neurosci., 6:37. doi: 10.3389/fncom.2012.00037, (in press) , 2012 Download
• Wibisono A., Bouvrie J., Rosasco L., Poggio T., Learning and Invariance in a Family of Hierarchical Kernels , CSAIL Technical Report, TR-2010-035 / CBCL-290, 2010 Download
• Masquelier T., Serre T., Thorpe S., Poggio T., Learning complex cell invariance from natural videos: A plausibility proof , CSAIL Technical Report, MIT-CSAIL-TR-2007-060/CBCL-269, 2007 Download
• Leibo J., Mutch J., Rosasco L., Ullman S., Poggio T., Learning Generic Invariances in Object Recognition: Translation and Scale , CSAIL Technical Report, MIT-CSAIL-TR-2010-061/CBCL-294, 2010 Download
• Diez Canas G., Poggio T., Rosasco L., Learning Manifolds with K-Means and K-Flats , Advances in Neural Information Processing Systems, , 2012 Download
• Mukherjee S., Niyogi P., Poggio T., Rifkin R., Mukherjee, S. 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
• Leibo J., Mutch J., Poggio T., Learning to discount transformations as the computational goal of visual cortex , CVPR 2011, , 2011 Download
• Bouvrie J., Ezzat T., Poggio T., Localized Spectro-Temporal Cepstral Analysis of Speech , ICASSP 2008 , , 2008
• Smale S., Rosasco L., Bouvrie J., Caponnetto A., Poggio T., 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 [DOI 10.1007/s10208-009-9049-1], 2010 Download
• Smale S., Rosasco L., Bouvrie J., Caponnetto A., Poggio T., Mathematics of the Neural Response , CSAIL Technical Report, MIT-CSAIL-TR-2008-070/ CBCL-276, 2008 Download
• Ezzat T., Poggio T., Bouvrie J., Max-Gabor Analysis and Synthesis of Spectrograms , ICSLP 2006, , 2006 Download
• Poggio T., Memories of a friend of Odile , Odile Crick: A Memorial Exhibition, curator Becky Cohen, The Salk Institute, 2007 Download
• Wolf L., Jhuang H., Hazan T., Modeling Appearances with Low-Rank SVM , CVPR '07, , 2007 Download
• Baldassarre L., Rosasco L., Barla A., Verri A., Multi-Output Learning via Spectral Filtering , CSAIL Technical Report, , 2011 Download
• Mutch J., Leibo J., Smale S., Rosasco L., Poggio T., Neurons That Confuse Mirror-Symmetric Object Views , CSAIL Technical Report, MIT-CSAIL-TR-2010-062/CBCL-295, 2010 Download
• Poggio T., Neuroscience: New Insights for AI? , WImBI 2006, , 2006 Download
• Rifkin R., Schutte K., Saad D., Bouvrie J., Glass J., Noise Robust Phonetic Classification with Linear Regularized Least Squares and Second-Order Features , ICASSP2007, , 2007 Download
• Mosci S., Rosasco L., Santoro M., Verri A., Villa S., Nonparametric Sparsity and Regularization , CSAIL Technical Report, MIT-CSAIL-TR-2011-041/CBCL-303, 2011 Download
• Rifkin R., Lippert R., Notes on Regularized Least-Squares , CSAIL Technical Report, MIT-CSAIL-TR-2007-025 CBCL-268, 2007 Download
• Bouvrie J., Rosasco L., Shakhnarovich G., Smale S., Notes on the Shannon Entropy of the Neural Response , CSAIL Technical Report, MIT-CSAIL-TR-2009-049/CBCL-281, 2009 Download
• Meyers E., Zhang Y., Bichot N., Serre T., Poggio T., Desimone R., Object decoding with attention in inferior temporal cortex , PNAS 2011, 108:8850-8855, 2011, 2011 Download
• Bileschi S., Object Detection at Multiple Scales Improves Accuracy , ICPR 2008, , 2008 Download
• LeCun Y., Lowe D., Malik J., Mutch J., Perona P., Poggio T., Object Recognition, Computer Vision, and the Caltech 101: A Response to Pinto et al. , PLoS Computational Biology, , 2008
• Yokono J., Poggio T., Object Recognition Using Boosted Oriented Filter Based Local Descriptors , IEEJ Trans. Electron. Inf. Syst., Volume 129, Issue 5, pp. 806-811 [DOI: 10.1541/ieejeiss.129.806], 2009 Download
• Kreiman G., Hung C., Kraskov ., Quiroga R., Poggio T., DiCarlo J., Object Selectivity of Local Field Potentials and Spikes in the Macaque Inferior Temporal Cortex , Neuron, Vol. 49, 433-445, 2006 Download
• Caponnetto A., Poggio T., Smale S., On a model of visual cortex: learning invariance and selectivity from image sequences , CSAIL Technical Report, MIT-CSAIL-TR-2008-030/CBCL-272, 2008 Download
• Bouvrie J., Rosasco L., Poggio T., On Invariance in Hierarchical Models , NIPS 2009, 162, 2009 Download
• Rosasco L., Belkin M., De Vito E., Belkin, M., De Vito, E. On Learning with Integral Operators , JMLR, 11, (2010) 905-934 , 2010 Download
• Poggio T., Voinea S., Rosasco L., Online Learning, Stability, and Stochastic Gradient Descent , Cornell University Library, , 2011 Download
• Caponnetto A., Optimal Rates for Regularization Operators in Learning Theory , CSAIL Technical Report, MIT-CSAIL-TR-2006-062/CBCL-264, 2006 Download
• Rifkin R., Bouvrie J., Schutte K., Chikkerur S., Kouh M., Ezzat T., Poggio T., Phonetic Classification Using Hierarchical, Feed-forward, Spectro-temporal Patch-based Architectures , CSAIL Technical Report, MIT-CSAIL-TR-2007-019/CBCL-267, 2007 Download
• Cao R., Higashikubo B., Cardin J., Knoblich U., Ramos R., Nelson M., Moore C., Brumberg J., Pinacidil induces vascular dilation and hyperemia in vivo and does not impact biophysical properties of neurons and astrocytes in vitro , Cleve. Clin. J. Med., vol. 76 Suppl 2 S80-S85 [doi: 10.3949/ccjm.76.s2.16], 2009 Download
• Roy J., Riesenhuber M., Poggio T., Miller E., , Riesenhuber, M., E.K. Miller, Prefrontal cortex activity during flexible categorization , The Journal of Neuroscience, 30(25):8519–8528; DOI:10.1523/JNEUROSCI.4837-09.2010, 2010 Download
• Isik L., Meyers E., Leibo J., Poggio T., Preliminary MEG decoding results , CSAIL Technical Report, MIT-CSAIL-TR-2012-010, CBCL-307, 2012 Download
• Reddy L., Tsuchyia N., Serre T., Reading the mind's eye: Decoding object information during mental imagery from fMRI patterns , Neuroimage, 50, pp. 818-825, doi:10.1167/9.8.782, 2010 Download
• Mroueh Y., Poggio T., Rosasco L., Regularization Predicts While Discovering Taxonomy , CSAIL Technical Report, MIT-CSAIL-TR-2011-029/CBCL-299, 2011 Download
• Serre T., Wolf L., Bileschi S., Riesenhuber M., Poggio T., Robust Object Recognition with Cortex-like Mechanisms , TPAMI , Vol. 29, No. 3 Page(s): 411 - 426 , 2007 Download
• Terashima Y., Scene Classification with a Biologically Inspired Method , CSAIL Technical Report, MIT-CSAIL-TR-2009-020/ CBCL-277, 2009 Download
• Lo Gerfo L., Rosasco L., Odone F., De Vito E., Verri A., Spectral Algorithms for Supervised Learning , NECO, 20: 1873-1897, 2008 Download
• Rosasco L., Lo Gerfo L., Rosasco L., Odone F., De Vito E. and Verri, A. Spectral Algorithms for Supervised Learning , NECO, 20: 1873-1897 [doi:10.1162/neco.2008.05-07-517], 2008 Download
• De Vito E., Rosasco L., Toigo A., Spectral Regularization for Support Estimation , NIPS 2010, , 2010 Download
• Ezzat T., Bouvrie J., Poggio T., Spectro-Temporal Analysis of Speech Using 2-D Gabor Filters , Interspeech 2007, , 2007 Download
• Caponnetto A., Rakhlin A., Stability Properties of Empirical Risk Minimization over Donsker Classes , JMLR, Vol. 7, 2565-2583, 2006 Download
• Wibisono A., Rosasco L., Poggio T., Sufficient Conditions for Uniform Stability of Regularization Algorithms , CSAIL Technical Report, MIT-CSAIL-TR-2009-060/CBCL284, 2009 Download
• Sullivan K., test publication , Perception , , 2012
• 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, 2011 Download
• Poggio T., The Levels of Understanding framework, revised , CSAIL Technical Report, MIT-CSAIL-TR-2012-014, CBCL-308, 2012 Download
• Tan C., Leibo J., Poggio T., eds Cipolla R., Battiato S., Farinella G.M. Throwing Down the Visual Intelligence Gauntlet , Machine Learning for Computer Vision, Studies in Computational Intelligence Vol. 411, 2012 Download
• Zoccolan D., Kouh M., Poggio T., DiCarlo J., Trade-off between object selectivity and tolerance in monkey inferotemporal cortex , The Journal of Neuroscience, Volume 27(45), pp.12292–12307, 2007 Download
• Lorusso M., Facoetti A., Cattaneo C., Presenti S., Galli R., Molteni M., Geiger G., Training visual-spatial attention in developmental dyslexia , Dyslexia in Children: New Research, 143-160, 2006
• Meyers E., Wolf L., Using Biologically Inspired Visual Features for Face Processing , IJCV , Vol 76, No. 1, 93-104, 2008 Download
• Poggio T., Ullman S., David Marr Vision , The MIT Press, ISBN-10: 0-262-51462-1, 2010
• Bouvrie J., Sinha P., Visual object concept discovery: Observations in congenitally blind children, and a computational approach , Neurocomputing, Volume 70, Issues 13-15, pp.2218-2233, 2007 Download
• Ostrovsky Y., Meyers E., Ganesh S., Mathur U., Sinha P., Visual Parsing After Recovery From Blindness , Psychological Science, Vol. 20, No. 12, Pages 1467-1491 [DOI: 10.1111/j.1467-9280.2009.02471.x], 2009 Download
• Poggio T., Geiger G., Werner Reichardt: the man and his scientific legacy , CSAIL Technical Report, MIT-CSAIL-TR-2011-011, CBCL-297, 2011 Download
• Chikkerur S., Serre T., Tan C., Poggio T., What and Where: A Bayesian inference theory of visual attention , Vision Research, doi: 10.1016 /j.visres.2010.05.013, 2010 Download
• Leibo J., Mutch J., Poggio T., Why The Brain Separates Face Recognition From Object Recognition , NIPS 2011, , 2011 Download
• Geiger G., Cattaneo C., Galli R., Pozzoli U., Lorusso M., Facoetti A., Molteni M., Wide and diffuse perceptual modes characterize dyslexics in vision and audition , Perception , Vol. 37, Issue 11, Pages 1745 – 1764, 2008 Download

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