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From Understanding Cortex to Building Intelligent Machines
MIT - Independent Activity Period Course
24-25 Jan., 2007 - Rm: 46-5193
Tomaso Poggio, Tony Ezzat & Thomas Serre
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A brief introduction to statistical learning theory will be followed by a description of highlights research in computational neuroscience at CBCL. The main thesis of the class is that progress in AI is increasingly dependent on advances in computational neuroscience. In the class we will review recent work on visual and auditory recognition. In particular,
- We will describe a theory of the computations and circuits underlying object recognition in the feedforward path of the ventral stream of visual cortex. We will also evaluate the performance of the cortical model versus performance of humans and machines.
- We will introduce a preliminary approach in the same spirit to the auditory cortex. Current approaches to various applications in speech processing such as speech separation, speech recognition, and speech synthesis will be discussed.
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Class 1: Wed 24 Jan, 10:00pm-1:00pm |
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Supplementary information: |
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Learning theory
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)
Poggio, T., R. Rifkin, S. Mukherjee and P. Niyogi. General Conditions for Predictivity in Learning Theory , Nature , Vol. 428, 419-422, 2004.
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Bioinformatics
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.
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Face detection
B. Heisele, T. Serre and T. Poggio. A component-based framework for face detection and identification. In: International Journal of Computer Vision, to appear , 2007
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Computer Graphics
Ezzat, T., G. Geiger and T. Poggio. Trainable Videorealistic Speech Animation . In: Proceedings of ACM SIGGRAPH 2002, San Antonio, TX, 388-398, 2002.
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Useful Links :
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Supplementary information: |
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Neuroscience / model overview:
T. Serre, 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, December, 2005
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Neuroscience / comparison between the model and human observers:
Serre, T., A. Oliva and T. Poggio. A Feedforward Theory of Visual Cortex Accounts for Human Performance in Rapid Categorization , CBCL Paper # MMVI-02 , Massachusetts Institute of Technology, Cambridge, MA, March, 2006.
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Computer vision / Comparison with benchmark AI systems:
T. Serre, L. Wolf, S. Bileschi, M. Riesenhuber and T. Poggio. Object recognition with cortex-like mechanisms. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 29 (3), pp. 411-426 , 2007
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Useful Links:
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Class 2: Thur 25 Jan, 10:00pm-12:00pm |
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Supplementary information:
R.P. Lippmann, Speech recognition by machines and humans, Speech Communication, 1997
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P. Rauschecker, B. Tian, Mechanisms and streams for processing of "what” and "where” in auditory
cortex, Proceedings of the National Academy of Sciences, 2000.
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| D.A. Depireux, J.Z. Simon, D.J. Klein, S.A. Shamma, Spectro-Temporal Response Field Characterization With Dynamic Ripples in Ferret Primary Auditory Cortex, Journal of Neurophysiology, 2001. |
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