Wenlong Mou - RankMe

37 papers A* 8Journal 27Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Continuous-time reinforcement learning: ellipticity enables model-free value function approximation. CoRR Wenlong Mou
2026	J	`jnl`	Predicting and improving test-time scaling laws via reward tail-guided search. CoRR Muheng Li, Jian Qian, Wenlong Mou
2025	J	`jnl`	Federated learning over physical channels: adaptive algorithms with near-optimal guarantees. CoRR Rui Zhang, Wenlong Mou
2025	J	`jnl`	Is RL fine-tuning harder than regression? A PDE learning approach for diffusion models. CoRR Wenlong Mou
2025	J	`jnl`	Reinforcement Learning with Action-Triggered Observations. CoRR Alexander Ryabchenko, Wenlong Mou
2025	J	`jnl`	Statistical guarantees for continuous-time policy evaluation: blessing of ellipticity and new tradeoffs. CoRR Wenlong Mou
2024	J	`jnl`	A Diffusion Process Perspective on Posterior Contraction Rates for Parameters. SIAM J. Math. Data Sci. Wenlong Mou, Nhat Ho, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2024	J	`jnl`	On Bellman equations for continuous-time policy evaluation I: discretization and approximation. CoRR Wenlong Mou, Yuhua Zhu
2024	J	`jnl`	To bootstrap or to rollout? An optimal and adaptive interpolation. CoRR Wenlong Mou, Jian Qian
2023	J	`jnl`	Optimal Oracle Inequalities for Projected Fixed-Point Equations, with Applications to Policy Evaluation. Math. Oper. Res. Wenlong Mou, Ashwin Pananjady, Martin J. Wainwright
2022	J	`jnl`	An Efficient Sampling Algorithm for Non-smooth Composite Potentials. J. Mach. Learn. Res. Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett
2022	J	`jnl`	Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency. CoRR Wenlong Mou, Martin J. Wainwright, Peter L. Bartlett
2022	A*	`conf`	Optimal and instance-dependent guarantees for Markovian linear stochastic approximation. COLT Wenlong Mou, Ashwin Pananjady, Martin J. Wainwright, Peter L. Bartlett
2022	J	`jnl`	Optimal variance-reduced stochastic approximation in Banach spaces. CoRR Wenlong Mou, Koulik Khamaru, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2022	A*	`conf`	ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm. COLT Chris Junchi Li, Wenlong Mou, Martin J. Wainwright, Michael I. Jordan
2021	J	`jnl`	High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm. J. Mach. Learn. Res. Wenlong Mou, Yi-An Ma, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2021	J	`jnl`	Optimal and instance-dependent guarantees for Markovian linear stochastic approximation. CoRR Wenlong Mou, Ashwin Pananjady, Martin J. Wainwright, Peter L. Bartlett
2020	A*	`conf`	On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration. COLT Wenlong Mou, Chris Junchi Li, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2020	J	`jnl`	On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration. CoRR Wenlong Mou, Chris Junchi Li, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2020	J	`jnl`	On the Sample Complexity of Reinforcement Learning with Policy Space Generalization. CoRR Wenlong Mou, Zheng Wen, Xi Chen
2020	J	`jnl`	Optimal oracle inequalities for solving projected fixed-point equations. CoRR Wenlong Mou, Ashwin Pananjady, Martin J. Wainwright
2020	J	`jnl`	ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm. CoRR Chris Junchi Li, Wenlong Mou, Martin J. Wainwright, Michael I. Jordan
2019	J	`jnl`	An Efficient Sampling Algorithm for Non-smooth Composite Potentials. CoRR Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett
2019	J	`jnl`	High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm. CoRR Wenlong Mou, Yi-An Ma, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2019	J	`jnl`	Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing. CoRR Wenlong Mou, Nhat Ho, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2018	A*	`conf`	Dropout Training, Data-dependent Regularization, and Generalization Bounds. ICML Wenlong Mou, Yuchen Zhou, Jun Gao, Liwei Wang
2018	A*	`conf`	Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints. COLT Wenlong Mou, Liwei Wang, Xiyu Zhai, Kai Zheng
2017	—	`conf`	A Refined Analysis of LSH for Well-dispersed Data Points. ANALCO Wenlong Mou, Liwei Wang
2017	A*	`conf`	Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible. ICML Kai Zheng, Wenlong Mou, Liwei Wang
2017	J	`jnl`	Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible. CoRR Kai Zheng, Wenlong Mou, Liwei Wang
2017	A*	`conf`	Differentially Private Clustering in High-Dimensional Euclidean Spaces. ICML Maria-Florina Balcan, Travis Dick, Yingyu Liang, Wenlong Mou, Hongyang Zhang
2017	A*	`conf`	Efficient Private ERM for Smooth Objectives. IJCAI Jiaqi Zhang, Kai Zheng, Wenlong Mou, Liwei Wang
2017	J	`jnl`	Efficient Private ERM for Smooth Objectives. CoRR Jiaqi Zhang, Kai Zheng, Wenlong Mou, Liwei Wang
2017	J	`jnl`	Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints. CoRR Wenlong Mou, Liwei Wang, Xiyu Zhai, Kai Zheng
2016	J	`jnl`	A Refined Analysis of LSH for Well-dispersed Data Points. CoRR Wenlong Mou, Liwei Wang
2016	J	`jnl`	Stable Memory Allocation in the Hippocampus: Fundamental Limits and Neural Realization. CoRR Wenlong Mou, Zhi Wang, Liwei Wang
2015	—	`conf`	Politicize and Depoliticize: A Study of Semantic Shifts on People's Daily Fifty Years' Corpus via Distributed Word Representation Space. CLSW Wenlong Mou, Ni Sun, Junhao Zhang, Zhixuan Yang, Junfeng Hu