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arXiv · 2001.04321

Accelerating Block Coordinate Descent for Nonnegative Tensor Factorization

Andersen Man Shun Ang·Jeremy E. Cohen·Nicolas Gillis·Le Thi Khanh Hien
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Abstract

This paper is concerned with improving the empirical convergence speed of block-coordinate descent algorithms for approximate nonnegative tensor factorization (NTF). We propose an extrapolation strategy in-between block updates, referred to as heuristic extrapolation with restarts (HER). HER significantly accelerates the empirical convergence speed of most existing block-coordinate algorithms for dense NTF, in particular for challenging computational scenarios, while requiring a negligible additional computational budget.

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Andersen Man Shun Ang, Jeremy E. Cohen, Nicolas Gillis, Le Thi Khanh Hien. 2020-01-13. Accelerating Block Coordinate Descent for Nonnegative Tensor Factorization. https://doi.org/10.1002/nla.2373

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