Meeting Minutes – 26 November 2008

Today, Paul R. Schrater a guest researcher from University Minnesota, has made a presentation about active preference learning topics. He explained a topic of probability model in which an agent can derive a continous valuation formula which is a result from learning algorithm from a set of discrete data. He tried to explained the algorithm which can decide what approximate formula can be presented to an individual in order to find the projected result that they value highly in as few trial as possible, without making an accurate model the entire valuation surface.



About the presenter,

Paul R. Schrater hold a joint faculty position at the University of Minnesota, in the departments of Psychology and Computer Science. His current research interests generally involve using probabilistic methods to study issues in perception and motor control. He received his Ph.D. from the Department of Neuroscience of the University of Pennsylvania, under David Knill, then of the Department of Psychology and Eero Simoncelli in the GRASP Laboratory who at that time had a primary appointment in the Department of Computer Science at Penn. His dissertation involved a psychophysical and ideal observer analysis of local motion processing.