5 papers
Smoothed Gradient Method for Nonconvex Federated Stochastic Bilevel Optimization
Xinwen Zhang, Peiran Yu, Zhaosong Lu +1
In recent years, federated stochastic bilevel optimization has attracted increasing attention due to its wide range of applications in machine learning. To reduce the computational…
A first-order method for nonconvex-strongly-concave constrained minimax optimization
Zhaosong Lu, Sanyou Mei
In this paper we study a nonconvex-strongly-concave constrained minimax problem. Specifically, we propose a first-order augmented Lagrangian method for solving it, whose subproblem…
A first-order method for constrained nonconvex-nonconcave minimax optimization
Zhaosong Lu, Xiangyuan Wang
We study a class of constrained nonconvex-nonconcave minimax optimization problems in which the inner maximization involves potentially complex constraints. Under the assumption th…
A first-order method for nonconvex-nonconcave minimax problems under a local Kurdyka-Lojasiewicz condition
Zhaosong Lu, Xiangyuan Wang
We study a class of nonconvex-nonconcave minimax problems in which the inner maximization problem satisfies a local Kurdyka-Lojasiewicz (KL) condition that may vary with the outer…
Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
Quanqi Hu, Qi Qi, Zhaosong Lu +1
In this paper, we study a class of non-smooth non-convex problems in the form of , where both a…