10 citations · 17 across the 26 of their papers we have counts for
13 papers · 1 filter
Variance-Aware Fine-Grained Gap-Dependent Bounds for Online Reinforcement Learning
Haochen Zhang, Lingzhou Xue, Zhong Zheng
We study model-free online reinforcement learning (RL) for episodic tabular Markov decision processes, focusing on both gap-dependent regret and policy switching cost. While fine-g…
Exact Fast Batch Simulation for Tabular Reinforcement Learning
Haochen Zhang, Lingzhou Xue, Zhong Zheng
Simulation is a fundamental computational primitive in reinforcement learning (RL), yet conventional simulation explicitly generates individual trajectories even when downstream pr…
Provably Efficient Federated Reinforcement Learning with Linear Function Approximation and Logarithmic Communication Cost
Zihang Liang, Haochen Zhang, Lingzhou Xue
We study federated online reinforcement learning with linear function approximation. While recent multi-agent reinforcement learning algorithms achieve strong regret guarantees, th…
SQL-RewriteBench: A Correctness-Gated, Full-Denominator Benchmark for Statement-Level SQL Rewriting [Experiment,Analysis & Benchmark]
Jiang Long, Tianci Gao, Shiyuan Hao +3
Statement-level SQL rewriting can improve query performance and maintainability without changing the DBMS kernel, but existing benchmarks do not evaluate rewrite methods as deploya…
Flatness Preserves Instruction Following in Vision-Language-Action Models
Haochen Zhang, Yonatan Bisk
Vision-language-action (VLA) models have the potential for open-world generalization by leveraging pretrained vision-language representations, yet downstream finetuning on limited…
Inductive Generalization for Robotic Manipulation
Annabella Macaluso, Haochen Zhang, Ishaan Masilamony +2
Understanding the generalization capabilities of visuomotor policies is essential in the development of capable robotic agents. Generalizable models learn structures that transfer…