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Given a large dataset of users' ratings of movies, what is the best model to accurately predict which movies a person will like? And how can we prevent spammers from tricking our algorithms into suggesting a bad movie? Is it possible to infer structure between movies simultaneously? In this paper we describe a unified Bayesian approach to Collaborative Filtering that accomplishes all of these goals. It models the discrete structure of ratings and is flexible to the often non-Gaussian shape ofdoi:10.1145/2566486.2568040 dblp:conf/www/BeutelMFS14 fatcat:jfc6bsoxzfahdd2usxjb2wuo2e