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Bregman Stochastic Proximal Point Algorithm with Variance Reduction
Cheik Traoré, Peter Ochs
Stochastic algorithms, especially stochastic gradient descent (SGD), have proven to be the go-to methods in data science and machine learning. In recent years, the stochastic proxi…
math.OC2025
A Proximal Stochastic Variance Reduced Zeroth-order Algorithm using Structured Finite-Differences
Marco Rando, Cheik Traoré, Cesare Molinari +2
Minimizing finite sums of functions is a central problem in optimization, arising in numerous practical applications. Such problems are commonly addressed using first-order optimiz…