137 citations · 656 across the 54 of their papers we have counts for
7 papers · 2 filters
Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
Batuhan Yardim, Semih Cayci, Matthieu Geist +1
Mean-field games have been used as a theoretical tool to obtain an approximate Nash equilibrium for symmetric and anonymous -player games. However, limiting applicability, exist…
Sharp Analysis of Stochastic Optimization under Global Kurdyka-Łojasiewicz Inequality
Ilyas Fatkhullin, Jalal Etesami, Niao He +1
We study the complexity of finding the global solution to stochastic nonconvex optimization when the objective function satisfies global Kurdyka-Lojasiewicz (KL) inequality and the…
TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization
Xiang Li, Junchi Yang, Niao He
Adaptive gradient methods have shown their ability to adjust the stepsizes on the fly in a parameter-agnostic manner, and empirically achieve faster convergence for solving minimiz…
Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization
Junchi Yang, Xiang Li, Niao He
Adaptive algorithms like AdaGrad and AMSGrad are successful in nonconvex optimization owing to their parameter-agnostic ability -- requiring no a priori knowledge about problem-spe…
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization
Siqi Zhang, Yifan Hu, Liang Zhang +1
This paper takes an initial step to systematically investigate the generalization bounds of algorithms for solving nonconvex-(strongly)-concave (NC-SC/NC-C) stochastic minimax opti…
Efficient Algorithms for A Class of Stochastic Hidden Convex Optimization and Its Applications in Network Revenue Management
Xin Chen, Niao He, Yifan Hu +1
We study a class of stochastic nonconvex optimization in the form of , i.e., is a composition of a convex function and…
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization
Kiran Koshy Thekumparampil, Niao He, Sewoong Oh
We study the bilinearly coupled minimax problem: , where and are both strongly convex smooth functions and admit first-order gra…