12 citations · 21 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
Statistical Convergence of the EM Algorithm on Gaussian Mixture Models
Ruofei Zhao, Yuanzhi Li, Yuekai Sun
We study the convergence behavior of the Expectation Maximization (EM) algorithm on Gaussian mixture models with an arbitrary number of mixture components and mixing weights. We sh…
The Well Tempered Lasso
Yuanzhi Li, Yoram Singer
We study the complexity of the entire regularization path for least squares regression with 1-norm penalty, known as the Lasso. Every regression parameter in the Lasso changes line…
A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model
Xi Chen, Yuanzhi Li, Jieming Mao
We study the active learning problem of top- ranking from multi-wise comparisons under the popular multinomial logit model. Our goal is to identify the top- items with high p…