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Article Dans Une Revue Numerical Linear Algebra with Applications Année : 2021

Accelerating Block Coordinate Descent for Nonnegative Tensor Factorization

Résumé

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.

Dates et versions

hal-03038513 , version 1 (03-12-2020)

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Andersen Man Shun Ang, Jérémy E Cohen, Nicolas Gillis, Le Thi Khanh Hien. Accelerating Block Coordinate Descent for Nonnegative Tensor Factorization. Numerical Linear Algebra with Applications, 2021, 28 (5), ⟨10.1002/nla.2373⟩. ⟨hal-03038513⟩
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