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Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction

2020-01-13 | |  76 |   37 |   0

Abstract

We present a probabilistic formulation of max-margin matrix factorization and build accordingly a nonparametric Bayesian model which automatically resolves 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 algorithm for posterior inference, and our extensive empirical studies on large-scale MovieLens and EachMovie data sets appear to justify the aforementioned dual advantages.

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