65 citations · 367 across the 30 of their papers we have counts for
5 papers · 1 filter
Neural Contextual Bandits with Deep Representation and Shallow Exploration
Pan Xu, Zheng Wen, Handong Zhao +1
We study a general class of contextual bandits, where each context-action pair is associated with a raw feature vector, but the reward generating function is unknown. We propose a…
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling
Difan Zou, Pan Xu, Quanquan Gu
We provide a new convergence analysis of stochastic gradient Langevin dynamics (SGLD) for sampling from a class of distributions that can be non-log-concave. At the core of our app…
A Finite Time Analysis of Two Time-Scale Actor Critic Methods
Yue Wu, Weitong Zhang, Pan Xu +1
Actor-critic (AC) methods have exhibited great empirical success compared with other reinforcement learning algorithms, where the actor uses the policy gradient to improve the lear…
MOTS: Minimax Optimal Thompson Sampling
Tianyuan Jin, Pan Xu, Jieming Shi +2
Thompson sampling is one of the most widely used algorithms for many online decision problems, due to its simplicity in implementation and superior empirical performance over other…
Double Explore-then-Commit: Asymptotic Optimality and Beyond
Tianyuan Jin, Pan Xu, Xiaokui Xiao +1
We study the multi-armed bandit problem with subgaussian rewards. The explore-then-commit (ETC) strategy, which consists of an exploration phase followed by an exploitation phase,…