33 citations · 93 across the 12 of their papers we have counts for
9 papers · 1 filter
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…
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…
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization
Siqi Zhang, Junchi Yang, Cristóbal Guzmán +2
This paper studies the complexity for finding approximate stationary points of nonconvex-strongly-concave (NC-SC) smooth minimax problems, in both general and averaged smooth finit…
Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems
Junchi Yang, Negar Kiyavash, Niao He
Nonconvex minimax problems appear frequently in emerging machine learning applications, such as generative adversarial networks and adversarial learning. Simple algorithms such as…
Bregman Augmented Lagrangian and Its Acceleration
Shen Yan, Niao He
We study the Bregman Augmented Lagrangian method (BALM) for solving convex problems with linear constraints. For classical Augmented Lagrangian method, the convergence rate and its…
A Unified Switching System Perspective and O.D.E. Analysis of Q-Learning Algorithms
Donghwan Lee, Niao He
In this paper, we introduce a unified framework for analyzing a large family of Q-learning algorithms, based on switching system perspectives and ODE-based stochastic approximation…