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20182025
most citedOn the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

37 citations · 60 across the 12 of their papers we have counts for

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Showing 2024 · math.OCShow all

2 papers · 2 filters

math.OC2024

Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization

Ruichen Jiang, Ali Kavis, Qiujiang Jin +2

We propose adaptive, line search-free second-order methods with optimal rate of convergence for solving convex-concave min-max problems. By means of an adaptive step size, our algo…

math.OC2024★ 1 cited

Universal Gradient Methods for Stochastic Convex Optimization

Anton Rodomanov, Ali Kavis, Yongtao Wu +2

We develop universal gradient methods for Stochastic Convex Optimization (SCO). Our algorithms automatically adapt not only to the oracle's noise but also to the Hölder smoothness…