12 citations · 21 across the 6 of their papers we have counts for
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cs.LG2021
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning
Yuanzhi Li, Ruosong Wang, Lin F. Yang
Recently there is a surge of interest in understanding the horizon-dependence of the sample complexity in reinforcement learning (RL). Notably, for an RL environment with horizon l…
cs.LG2021★ 2 cited
On the One-sided Convergence of Adam-type Algorithms in Non-convex Non-concave Min-max Optimization
Zehao Dou, Yuanzhi Li
Adam-type methods, the extension of adaptive gradient methods, have shown great performance in the training of both supervised and unsupervised machine learning models. In particul…
cs.LG2020★ 1 cited
Making Method of Moments Great Again? -- How can GANs learn distributions
Yuanzhi Li, Zehao Dou
Generative Adversarial Networks (GANs) are widely used models to learn complex real-world distributions. In GANs, the training of the generator usually stops when the discriminator…