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Bayesian Nonparametric Maximum Margin Matrix Factorization for Collaborative Prediction
Minjie Xu · Jun Zhu · Bo Zhang

Mon Dec 03 07:00 PM -- 12:00 AM (PST) @ Harrah’s Special Events Center 2nd Floor

We present a probabilistic formulation to max-margin matrix factorization and build accordingly an infinite nonparametric Bayesian model to automatically resolve the unknown number of latent factors. Our work demonstrates a successful example that integrates Bayesian nonparametrics and max-margin learning, which are conventionally two separate paradigms and enjoy complementary advantages. We develop an efficient variational learning algorithm for posterior inference, and our extensive empirical studies on large-scale MovieLens and EachMovie data sets appear to demonstrate the advantages inherited from both max-margin matrix factorization and Bayesian nonparametrics.

Author Information

Minjie Xu (Bloomberg LP)
Jun Zhu (Tsinghua University)
Bo Zhang (Fair Isaac Corp.)

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