priors as compared to a prior-free version of the bandit algorithm.
Background paper: http://portal.acm.org/citation.cfm?id=1639714.1639737
Paul Resnick is a Professor at the University of Michigan School of Information. He previously worked as a researcher at AT&T Labs and AT&T Bell Labs, and as an Assistant Professor at the MIT Sloan School of Management. He received the master’s and Ph.D. degrees in Electrical Engineering and Computer Science from MIT, and a bachelor’s degree in mathematics from the University of Michigan.
Professor Resnick’s research focuses on SocioTechnical Capital, productive social relations that are enabled by the ongoing use of information and communication technology. His current projects include analyzing and designing reputation systems, ride share coordination services, and applying principles from economics and social psychology to the design of on-line communities.
Resnick was a pioneer in the field of recommender systems (sometimes called collaborative filtering or social filtering). Recommender systems guide people to interesting materials based on recommendations from other people. His articles have appeared in Scientific American, Wired, Communications of the ACM, The American Economic Review, Management Science, and many other publications.