arXiv Machine Learning By Dmitrii M. Ostrovskii, Babak Barazandeh, Meisam Razaviyayn

Nonconvex-Nonconcave Min-Max Optimization with a Small Maximization Domain

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arXiv:2110. 03950v3 Announce Type: replace-cross Abstract: We study the problem of finding approximate first-order stationary points in optimization problems of the form $\min_{x \in X} \max_{y \in Y} f(x,y)$, where the sets $X,Y$ are convex and $Y$ is compact.

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arXiv Machine Learning
Aug 10

A proximal subgradient method for nonconvex stochastic optimization under the Kurdyka-{\L}ojasiewicz condition

arXiv:2608. 05460v1 Announce Type: cross Abstract: This work introduces a proximal stochastic subgradient method for minimizing the sum of an expected cost, whose integrand is potentially nonsmooth and nonconvex, and a lower semicontinuous, prox-bounded function.

By Felipe Atenas, Alejandro Jofr\'e, Pedro P\'erez-Aros, David Torregrosa-Bel\'en
arXiv Machine Learning
Jun 15

Online Convex Optimization with Sublinear Noisy Probes

arXiv:2606. 14640v1 Announce Type: new Abstract: We study Online Convex Optimization (OCO) over a convex set $K\subseteq \mathbb R^d$, where in each round $t$ the learner selects $x_t\in K$ and then observes a convex loss $f_t:K\to[0,1]$, with the goal of minimizing regret to the best fixed decision in hindsight.

By Simone Di Gregorio, Anupam Gupta, Stefano Leonardi, Matteo Russo