Applied Statistics - Charles Kemp and Josh Tenenbaum 

 This week, the Applied Statistics Workshop will be presenting a talk by Charles Kemp and Josh Tenenbaum of the Department of Brain and Cognitive Sciences at MIT.  Their presentation, "Bayesian Models of Human Learning and Reasoning," will look at the way individuals make generalizations based on limited experience.  The presenters argue that these generalizations should be thought of as Bayesian inferences over structured probabilistic models.   

  Charles Kemp  is a Ph.D. student in the Department of Brain and Cognitive Sciences at MIT.  He hails from Australia, and he received his undergraduate degree from the University of Melbourne.  His research focuses on formal models of semantic knowledge and the use of those models for inductive inference.    Josh Tenenbaum  is the Paul E. Newman Career Development Professor in the Department of Brain and Cognitive Sciences.  After receiving his Ph.D. from MIT in 1999, he joined  the faculty at Stanford University, returning to MIT in 2002.  He has published widely on the topic of human learning and inference, drawing on modeling methodologies including Bayesian statistics, graph theory, and the geometry of manifolds. 

 The presentation will be at noon on Wednesday, October 19 in Room N354, CGIS North, 1737 Cambridge St. Lunch will be provided.