Momentum-based variance-reduced stochastic Bregman proximal gradient methods for nonconvex nonsmooth optimization

S. Liao; Yan Liu; Congying Han; Tiande Guo

doi:10.1016/j.eswa.2024.125960

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Momentum-based variance-reduced stochastic Bregman proximal gradient methods for nonconvex nonsmooth optimization

S. Liao Yan Liu Congying Han Tiande Guo

Year: 2024 Journal: Expert Systems with Applications Vol: 266 Pages: 125960-125960 Publisher: Elsevier BV

DOI: 10.1016/j.eswa.2024.125960

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Keywords:

Variance (accounting) Momentum (technical analysis) Bregman divergence Applied mathematics Mathematical optimization Mathematics Stochastic optimization Computer science

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Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

Stochastic Gradient Optimization Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Markov Chains and Monte Carlo Methods

Physical Sciences → Mathematics → Statistics and Probability

Momentum-based variance-reduced stochastic Bregman proximal gradient methods for nonconvex nonsmooth optimization

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