1. Emmanuel Guigon. Interpolation and extrapolation in human behavior.. Journal of Cognitive Neuroscience, 16(3), 2004.
   Keywords: motor control, sensorimotor. [Abstract] [Comments] [bibtex-entry]



2. Emanuel Todorov. Optimality principles in sensorimotor control. Nature Neuroscience, 7(9):907-915, 2004.
   Keywords: neuroscience, motor control, internal models, feedback, minimum variance. [Abstract] [Comments] [bibtex-entry]



3. Paul Bach-y-Rita, Mitchell E. Tyler, and Kurt A. Kaczmarek. Seeing with the brain. Internation journal of human-computer interaction, 15(2):285-295, 2003.
   Keywords: vision, sensory substitution. [Abstract] [bibtex-entry]



4. Rony Paz, Thomas Boraud, Chen Natan, Hagai Bergman, and Eilon Vaadia. Preparatory activity in motor cortex reflects learning of local visuomotors skills. Nature Neuroscience, 6(8):882-890, 2003.
   Keywords: motor control, NCC. [Abstract] [Comments] [bibtex-entry]



5. D. M. Wolpert, Z. Ghahramani, and J. R. Flanagan. Perspectives and Problems in Motor Learning. TRENDS in Cognitive Sciences, 5(11):487-494, november 2001.
   Keywords: motor control, physiology. [Comments] [bibtex-entry]



6. jacob Feldman. Minimization of Boolean complexity in human concept learning. Nature, 407:63-633, 2000.
   Keywords: complexity, logic. [Abstract] [Comments] [bibtex-entry]



7. S. T. Roweis and L. K. Saul. Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science, 290:2323-2326, December 2000.
   Keywords: geometry, dimension reduction. [Abstract] [bibtex-entry]



8. Shun-Ichi Amari. Natural Gradient Learning for Over- and Under-Complete Bases in ICA. Neural Computation, 1999.
   Keywords: ICA, statistics, neural networks. [Abstract] [Comments] [bibtex-entry]



9. Mitsuo Kawato. Internal models for motor control and trajectory planning. Current Opinion in Neurobiology, 9:718-727, 1999.
   Keywords: neuroscience, motor control, internal models. [Abstract] [Comments] [bibtex-entry]



10. D. D. Lee and H. S. Seung. Learning the Parts of Objects by Non-negative Matrix Factorization. Nature, 401:788, october 1999.
    Keywords: mathematics, ingeneering, artificial vision, decomposition. [Abstract] [Comments] [bibtex-entry]



11. Zenon Pylyshyn. Is Vision Continuous With Cognition? The Case for Cognitive Impenetrability of Visual Perception. Behavioral and Brain Sciences, 22(3), 1999.
    Keywords: vision, cognition, perception. [Abstract] [bibtex-entry]



12. S. Zeki, S. Aglioti, D. McKeefry, and G. Berlucchi. The neurological basis of conscious color perception in a blind patient. Proceedings of the National Academy of Sciences, 96(24), 1999.
    Keywords: neuroscience, blind, vision, perception, NCC. [Abstract] [bibtex-entry]



13. A.J. Bell and T.J. Sejnowski. The 'independent components' of natural scenes are edge filters. Vision Research, (37):3327-3338, 1997.
    Keywords: information theory. [Abstract] [bibtex-entry]



14. Shimon Edelman and Nathan Intrator. Learning as extraction of low-dimensional representations. november 1997.
    Keywords: dimension reduction, learning. [Abstract] [bibtex-entry]



15. David Pierce and Benjamin Kuipers. Map learning with Uninterpreted Sensors and Effectors. Artificial Intelligence, 92:169-229, 1997.
    Keywords: artificial intelligence, learning. [Abstract] [Comments] [bibtex-entry]



16. B.A. Olshausen and D.J. Field. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381:607-609, 1996.
    Keywords: vision, ICA, information theory. [Abstract] [bibtex-entry]



17. Antony J. Bell and Terrence J. Sejnowski. An information maximisation approach to blind separation and blind deconvolution. Neural Computation, 7(6):1129-1159, 1995.
    Keywords: statistics, ICA, information theory. [Abstract] [bibtex-entry]



18. Patricia Churchland. Can Neurobiology teach us anything about consciousness ?. Proceedings and Adresses of the American Philosophical Association, 1994.
    Keywords: consciousness, NCC. [Abstract] [bibtex-entry]



19. J. Droulez and A. Berthoz. A neural network model of sensoritopic maps with predictive short-term memory properties. Proceedings of the National Academy of Sciences, 88:9653-9657, 1991.
    Keywords: neural networks, neuroscience. [Abstract] [bibtex-entry]



20. C. Blakemore and D. E. Mitchell. Environmental modification of the visual cortex and the neural basis of learning and memory. Nature, 241:467-468, 1973.
    Keywords: neuroscience, sensation, perception, vision. [bibtex-entry]

1. Ernst (von) Glasersfled. Scheme Theory as a key to the learning paradox. In , 2001.
   Keywords: learning, philosophy. [Abstract] [Comments] [bibtex-entry]



2. F. Meinecke, A. Ziehe, M. Kawanabe, and K-R Müller. Assessing Reliability of ICA Projections - a Resampling Approach. In ICA 2001, 2001.
   Keywords: ICA, statistics, BSS. [Abstract] [Comments] [bibtex-entry]



3. H Lappalainen and J. W. Miskin. Ensemble Learning. In , 2000.
   Keywords: Bayes, probabilities, statistics. [Abstract] [bibtex-entry]

1. J. J. Verbeek, N. Vlassis, and B. Kröse. Coordinating Mixtures of Probabilistic Principal Component Analyzers. Technical report, Computer Science Institute, University of Amsterdam, The Netherlands, February 2002. Note: IAS-UVA-02-01.
   Keywords: statistics, PCA. [Abstract] [bibtex-entry]

1. Yoav Freund. homepage.
   Keywords: homepage, learning, computer science. [bibtex-entry]

All the ressources below are referenced through direct links, for easier use as a library of introductory and comprehensive papers on various subjects. If a paper of yours is on this list and you do not want your homepage to be bypassed, just send me an email.

Comments and ratings are for personnal use, they do not claim to reflect academic value. It is only an indication of their relevance with respect to my own interests and the success they happened to have in the scientific community.

This document was translated from BibT_EX by bibtex2html