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math.OC2026
Adaptive Bregman Proximal Stochastic Gradient with a Stabilized Barzilai--Borwein Step Size
Chenhan Jin, Shengze Xu, Binghui Xie +4
Bregman proximal stochastic gradient (BPSG) methods bring variance-reduced composite optimization to objectives whose geometry is poorly captured by Euclidean smoothness. Their per…
math.OC2021
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
We show that stochastic acceleration can be achieved under the perturbed iterate framework (Mania et al., 2017) in asynchronous lock-free optimization, which leads to the optimal i…