Learning from sparse data: Statistical inference in infants and children
Much of developmental research on infants and young children has focused on either how much innate knowledge infants have or how infants learn by keeping track of input statistics from their environment. Recent research aims to break this impasse between innate knowledge and learning by focusing on how children make principled generalizations based on limited amounts of data. Prof. Xu will describe a number of recent studies on probabilistic reasoning, social cognition, and language to illustrate that infants and young children have several powerful inductive learning mechanisms that allow for rapid acquisition of knowledge in various domains.
Tuesday, October 12, 2010
Friday, October 8, 2010
Fall 2010 Brown Bag Schedule
October 6:
Ron Dahl, School of Public Health, University of California, Berkeley
October 20:
Fei Xu, Department of Psychology, University of California, Berkeley
November 10:
Melanie Killen: Department of Human Development, University of Maryland
December 1: Andrew Fuligni, School of Medicine, University of California, Los Angeles
Brown Bag Meetings are held on Wednesdays, 12-1:30p.m. in Room 1111 Tolman Hall
Ron Dahl, School of Public Health, University of California, Berkeley
October 20:
Fei Xu, Department of Psychology, University of California, Berkeley
November 10:
Melanie Killen: Department of Human Development, University of Maryland
December 1: Andrew Fuligni, School of Medicine, University of California, Los Angeles
Brown Bag Meetings are held on Wednesdays, 12-1:30p.m. in Room 1111 Tolman Hall
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