Tuesday, April 7, 2009

Apr 22, 2009: James L. McClelland

Does Your Brain Use Symbols or Distributed Representations?


I will describe research on semantic cognition that relies on distributed representations instead of symbols. I will describe models that use distributed representations to explain a lot of phenomena in child development, adult cognition, and the disintegration of conceptual knowledge in a disorder called semantic dementia. Among the aspects of semantic cognition addressed are differentiation and reorganization of conceptual knowledge in development, domain and context specificity of inductive inference, semantic illusions, and conceptual grounding of knowledge from one domain in knowledge from another domain. The approach will be compared with the symbolic structured Bayesian approach taken by others.

Speaker Bio

Dr. James McClelland , Stanford University - Center for Mind, Brain and Computation

Jay McClelland received his Ph.D. in Cognitive Psychology from the University of Pennsylvania in 1975. He served on the faculty of the University of California, San Diego, before moving to Carnegie Mellon in 1984, where he became a University Professor and held the Walter Van Dyke Bingham Chair in Psychology and Cognitive Neuroscience. He was a founding Co-Director of the Center for the Neural Basis of Cognition, a joint project of Carnegie Mellon and the University of Pittsburgh. He served as Co-Director until 2006. In that year he moved to Stanford University, where he is now Professor of Psychology and founding Director of the Center for Mind, Brain and Computation.

Over his career, McClelland has contributed to both the experimental and theoretical literatures in a number of areas, most notably in the application of connectionist/parallel distributed processing models to problems in perception, cognitive development, language learning, and the neurobiology of memory. He was a co-founder with David E. Rumelhart of the Parallel Distributed Processing research group, and together with Rumelhart he led the effort leading to the publication in 1986 of the two-volume book, Parallel Distributed Processing, in which the parallel distributed processing framework was laid out and applied to a wide range of topics in cognitive psychology and cognitive neuroscience.

McClelland and Rumelhart jointly received the 1993 Howard Crosby Warren Medal from the Society of Experimental Psychologists, the 1996 Distinguished Scientific Contribution Award (see citation) from the American Psychological Association, the 2001 Grawemeyer Prize in Psychology, and the 2002 IEEE Neural Networks Pioneer Award for this work. McClelland has served as Senior Editor of Cognitive Science, as President of the Cognitive Science Society, and as a member of the National Advisory Mental Health Council, and he is currently president-elect of the Federation of the Behavioral, Psychological, and Cognitive Sciences. He is a member of the National Academy of Sciences, and he has received the APS William James Fellow Award for lifetime contributions to the basic science of psychology.

McClelland currently teaches cognitive psychology and cognitive neuroscience and conducts research on learning, memory, conceptual development, spoken language, decision making, and semantic cognition.

Refreshments will be served in MSC 159 after the talk.

Sunday, March 22, 2009

FLICS extra

As a service to our friends in the Greater Delaware Valley area who appreciate a FLICS, here is a talk in Philadelphia this week -- JD


Copyright vs. Community in the Age of Computer Networks
Richard M. Stallman
Free Software Foundation
March 25, 2009, 2-3:30pm
Kiva Auditorium at Temple University
Abstract (PDF)

Monday, February 16, 2009

Mar 18: Jennifer Golbeck @ Haverford

Computing with Social Trust: Web Algorithms, Social Networks, and Recommendations

Jennifer Golbeck
University of Maryland, College Park

Wednesday March 18
4:30 pm (tea at 4:00 pm)

Koshland INSC, Hilles 109
Haverford College
Directions to Campus
Campus Map (park in 45 or 53; talk in 5b)

Web-based social networks provide a wealth of publicly accessible information about people and their relationships. The trust between people in these is particularly interesting because it can be used to improve the way users access and interact with information especially user-generated content on the web. In this talk, I will present research on the two most important problems in this space. First, I will discuss methods for computing trust between people online, relying on graph algorithms and statistical analysis of user behavior and interaction. Then, I will show how these results can be used in applications where users interact with web-based information. In particular, we will look at recommender systems and see when and how trust can improve the quality of the results.

Tuesday, January 27, 2009

Feb 6: Bernard Chazelle at Bryn Mawr

What an iPod, a Flock of Birds, and Your DNA have in Common

A Colloquium by Bernard Chazelle, Princeton University

Friday, Feb 6th, 4:00-5:00p (Tea at 3:30p) in Room 338, Park Science Building

This is part of the Fantastic Lectures in Computer Science (FLICS) lecture series jointly sponsored by Bryn Mawr, Haverford, Swarthmore and Villanova.

For more information on FLICS, please check out:

Moore's Law holds that, every 18 months, computing power doubles. Most of the wonders of the computer age can be attributed directly to Moore's Law. Alas, its days are numbered. What then? In this talk, I will argue that the years ahead will usher in the era of the "Algorithm," a notion that might prove just as disruptive as the revolution in the physical sciences was in the last century. I will discuss why algorithms are even more powerful than customarily believed but why they will not unleash their true potential until they become full-fledged scientific tools and not just problem-solvers.


Bernard Chazelle is Eugene Higgins Professor of Computer Science at Princeton University, where he has been on the faculty since 1986. He has held research and faculty positions at Carnegie-Mellon University, Brown University, Ecole Polytechnique, Ecole Normale Superieure, University of Paris, INRIA, Xerox Parc, DEC SRC, and NEC Research, where he was a Fellow for many years. He received his Ph.D in computer science from Yale University in 1980. He is the author of the book "The Discrepancy Method."

Fellow, American Academy of Arts and Sciences
Member, European Academy of Sciences
Fellow, World Innovation Foundation
ACM Fellow
Guggenheim Fellow (1994)