title: Learning in brains and machines.
abstract: The problem of learning is arguably at the very core of the problem of intelligence, both biological and artificial. In this paper we sketch some of our work over the last ten years in the area of supervised learning, focusing on three interlinked directions of research: theory, engineering applications (that is, making intelligent software) and neuroscience (that is, understanding the brain's mechanisms of learning).
authors.affiliation: Center for Biological and Computational Learning, Massachusetts Institute of Technology, Cambridge 02139, USA.
authors.forename: T
authors.initials: T
authors.lastname: Poggio
authors.forename: C R
authors.initials: CR
authors.lastname: Shelton
mesh_terms: D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D007858:Learning / Q000502:physiology; D016571:Neural Networks, Computer; D014785:Vision, Ocular / Q000502:physiology*