3 citations · 4 across the 2 of their papers we have counts for
4 papers
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
Zixiang Chen, Chris Junchi Li, Angela Yuan +2
With the increasing need for handling large state and action spaces, general function approximation has become a key technique in reinforcement learning (RL). In this paper, we pro…
Self-training Converts Weak Learners to Strong Learners in Mixture Models
Spencer Frei, Difan Zou, Zixiang Chen +1
We consider a binary classification problem when the data comes from a mixture of two rotationally symmetric distributions satisfying concentration and anti-concentration propertie…
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks
Zixiang Chen, Yuan Cao, Quanquan Gu +1
A recent breakthrough in deep learning theory shows that the training of over-parameterized deep neural networks can be characterized by a kernel function called \textit{neural tan…
Stein Neural Sampler
Tianyang Hu, Zixiang Chen, Hanxi Sun +3
We propose two novel samplers to generate high-quality samples from a given (un-normalized) probability density. Motivated by the success of generative adversarial networks, we con…