Begin: Tue, 18. of Sep 2012 ( 7:00 PM)
Location: HNF
On September 18, 2012, Prof. Dr. Leslie G. Valiant from the Harvard University in Cambridge, USA, will give a talk about "Machine Learning and Beyond" in the context of the SFB 901 colloquium and in cooperation with the HNF.
Abstract:
Machine learning is a highly effective technology that has found broad applications
in science and technology. Behind it is a mathematical science that first defines the goals that
need to be achieved if learning is to be successful. It goes on to study the most effective ways
of achieving these goals, and also to characterize cases where effective learning is impossible.
However, central as this study may be for cognition, it does not account for all of cognition.
The question we ask here is whether one can build on the success of machine learning to
address the broader goals of artificial intelligence. We regard reasoning as the other main
component, and suggest that the central challenge is to unify learning and reasoning into a
single framework.
Information about the speaker:
Leslie Valiant was educated at King's College, Cambridge; Imperial College, London; and at
Warwick University where he received his Ph.D. in computer science in 1974. He is currently
T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics in the School
of Engineering and Applied Sciences at Harvard University, where he has taught since 1982.
Before coming to Harvard he had taught at Carnegie Mellon University, Leeds University,
and the University of Edinburgh.
His work has ranged over several areas of theoretical computer science, particularly
complexity theory, computational learning, and parallel computation. He also has interests in
computational neuroscience, evolution and artificial intelligence.
He received the Nevanlinna Prize at the International Congress of Mathematicians in 1986,
the Knuth Award in 1997, the European Association for Theoretical Computer Science
EATCS Award in 2008, and the 2010 A. M. Turing Award. He is a Fellow of the Royal
Society (London) and a member of the National Academy of Sciences (USA).
