Wenlong Mou

According to our database, Wenlong Mou authored at least 18 papers between 2015 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency.

Wenlong Mou, Martin J. Wainwright, Peter L. Bartlett

CoRR, 2022

Optimal variance-reduced stochastic approximation in Banach spaces.

Wenlong Mou, Koulik Khamaru, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan

CoRR, 2022

Optimal and instance-dependent guarantees for Markovian linear stochastic approximation.

Wenlong Mou, Ashwin Pananjady, Martin J. Wainwright, Peter L. Bartlett

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm.

Chris Junchi Li, Wenlong Mou, Martin J. Wainwright, Michael I. Jordan

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

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

2020

Optimal oracle inequalities for solving projected fixed-point equations.

Wenlong Mou, Ashwin Pananjady, Martin J. Wainwright

CoRR, 2020

On the Sample Complexity of Reinforcement Learning with Policy Space Generalization.

Wenlong Mou, Zheng Wen, Xi Chen

CoRR, 2020

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

Proceedings of the Conference on Learning Theory, 2020

2019

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

2018

Dropout Training, Data-dependent Regularization, and Generalization Bounds.

Wenlong Mou, Yuchen Zhou, Jun Gao, Liwei Wang

Proceedings of the 35th International Conference on Machine Learning, 2018

Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints.

Wenlong Mou, Liwei Wang, Xiyu Zhai, Kai Zheng

Proceedings of the Conference On Learning Theory, 2018

2017

Efficient Private ERM for Smooth Objectives.

Jiaqi Zhang, Kai Zheng, Wenlong Mou, Liwei Wang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Differentially Private Clustering in High-Dimensional Euclidean Spaces.

Maria-Florina Balcan, Travis Dick, Yingyu Liang, Wenlong Mou, Hongyang Zhang

Proceedings of the 34th International Conference on Machine Learning, 2017

Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible.

Kai Zheng, Wenlong Mou, Liwei Wang

Proceedings of the 34th International Conference on Machine Learning, 2017

A Refined Analysis of LSH for Well-dispersed Data Points.

Wenlong Mou, Liwei Wang

Proceedings of the Fourteenth Workshop on Analytic Algorithmics and Combinatorics, 2017

2016

Stable Memory Allocation in the Hippocampus: Fundamental Limits and Neural Realization.

Wenlong Mou, Zhi Wang, Liwei Wang

CoRR, 2016

2015

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

Proceedings of the Chinese Lexical Semantics - 16th Workshop, 2015