137 citations · 656 across the 54 of their papers we have counts for
5 papers · 1 filter
The Mean-Squared Error of Double Q-Learning
Wentao Weng, Harsh Gupta, Niao He +2
In this paper, we establish a theoretical comparison between the asymptotic mean-squared error of Double Q-learning and Q-learning. Our result builds upon an analysis for linear st…
Periodic Q-Learning
Donghwan Lee, Niao He
The use of target networks is a common practice in deep reinforcement learning for stabilizing the training; however, theoretical understanding of this technique is still limited.…
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…
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
Yifan Hu, Siqi Zhang, Xin Chen +1
Conditional stochastic optimization covers a variety of applications ranging from invariant learning and causal inference to meta-learning. However, constructing unbiased gradient…