Politicize and Depoliticize: A Study of Semantic Shifts on People's Daily Fifty Years' Corpus via Distributed Word Representation Space. - Wenlong Mou; Ni Sun; Junhao Zhang; Zhixuan Yang; Junfeng Hu (CLSW, 2015)

Stable Memory Allocation in the Hippocampus: Fundamental Limits and Neural Realization. - Wenlong Mou; Zhi Wang; Liwei Wang 001 (CoRR, 2016)

A Refined Analysis of LSH for Well-dispersed Data Points. - Wenlong Mou; Liwei Wang 001 (ANALCO, 2017)

Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible. - Kai Zheng 007; Wenlong Mou; Liwei Wang 001 (ICML, 2017)

Differentially Private Clustering in High-Dimensional Euclidean Spaces. - Maria-Florina Balcan; Travis Dick; Yingyu Liang; Wenlong Mou; Hongyang Zhang 001 (ICML, 2017)

Efficient Private ERM for Smooth Objectives. - Jiaqi Zhang; Kai Zheng 007; Wenlong Mou; Liwei Wang 001 (IJCAI, 2017)

Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints. - Wenlong Mou; Liwei Wang 001; Xiyu Zhai; Kai Zheng 007 (COLT, 2018)

Dropout Training, Data-dependent Regularization, and Generalization Bounds. - Wenlong Mou; Yuchen Zhou; Jun Gao 004; Liwei Wang 001 (ICML, 2018)

Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing. - Wenlong Mou; Nhat Ho; Martin J. Wainwright; Peter L. Bartlett; Michael I. Jordan (CoRR, 2019)

On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration. - Wenlong Mou; Chris Junchi Li; Martin J. Wainwright; Peter L. Bartlett; Michael I. Jordan (COLT, 2020)

On the Sample Complexity of Reinforcement Learning with Policy Space Generalization. - Wenlong Mou; Zheng Wen; Xi Chen (CoRR, 2020)

Optimal oracle inequalities for solving projected fixed-point equations. - Wenlong Mou; Ashwin Pananjady; Martin J. Wainwright (CoRR, 2020)

High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm. - Wenlong Mou; Yi-An Ma; Martin J. Wainwright; Peter L. Bartlett; Michael I. Jordan (J. Mach. Learn. Res., 2021)

ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm. - Chris Junchi Li; Wenlong Mou; Martin J. Wainwright; Michael I. Jordan (COLT, 2022)

Optimal and instance-dependent guarantees for Markovian linear stochastic approximation. - Wenlong Mou; Ashwin Pananjady; Martin J. Wainwright; Peter L. Bartlett (COLT, 2022)

Optimal variance-reduced stochastic approximation in Banach spaces. - Wenlong Mou; Koulik Khamaru; Martin J. Wainwright; Peter L. Bartlett; Michael I. Jordan (CoRR, 2022)

Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency. - Wenlong Mou; Martin J. Wainwright; Peter L. Bartlett (CoRR, 2022)

An Efficient Sampling Algorithm for Non-smooth Composite Potentials. - Wenlong Mou; Nicolas Flammarion; Martin J. Wainwright; Peter L. Bartlett (J. Mach. Learn. Res., 2022)

Optimal Oracle Inequalities for Projected Fixed-Point Equations, with Applications to Policy Evaluation. - Wenlong Mou; Ashwin Pananjady; Martin J. Wainwright (Math. Oper. Res., 2023)

On Bellman equations for continuous-time policy evaluation I: discretization and approximation. - Wenlong Mou; Yuhua Zhu (CoRR, 2024)

To bootstrap or to rollout? An optimal and adaptive interpolation. - Wenlong Mou; Jian Qian (CoRR, 2024)

A Diffusion Process Perspective on Posterior Contraction Rates for Parameters. - Wenlong Mou; Nhat Ho; Martin J. Wainwright; Peter L. Bartlett; Michael I. Jordan (SIAM J. Math. Data Sci., 2024)

Statistical guarantees for continuous-time policy evaluation: blessing of ellipticity and new tradeoffs. - Wenlong Mou (CoRR, 2025)