Approximate Method of Variational Bayesian Matrix Factorization/Completion with Sparse Prior

14 Mar 2018 Ryota Kawasumi Koujin Takeda

We derive analytical expression of matrix factorization/completion solution by variational Bayes method, under the assumption that observed matrix is originally the product of low-rank dense and sparse matrices with additive noise. We assume the prior of sparse matrix is Laplace distribution by taking matrix sparsity into consideration... (read more)

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