Wenlong Mou

According to our database1, Wenlong Mou authored at least 22 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Diffusion Process Perspective on Posterior Contraction Rates for Parameters.
SIAM J. Math. Data Sci., 2024

To bootstrap or to rollout? An optimal and adaptive interpolation.
CoRR, 2024

On Bellman equations for continuous-time policy evaluation I: discretization and approximation.
CoRR, 2024

2023
Optimal Oracle Inequalities for Projected Fixed-Point Equations, with Applications to Policy Evaluation.
Math. Oper. Res., 2023

2022
An Efficient Sampling Algorithm for Non-smooth Composite Potentials.
J. Mach. Learn. Res., 2022

Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency.
CoRR, 2022

Optimal variance-reduced stochastic approximation in Banach spaces.
CoRR, 2022

Optimal and instance-dependent guarantees for Markovian linear stochastic approximation.
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.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm.
J. Mach. Learn. Res., 2021

2020
Optimal oracle inequalities for solving projected fixed-point equations.
CoRR, 2020

On the Sample Complexity of Reinforcement Learning with Policy Space Generalization.
CoRR, 2020

On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration.
Proceedings of the Conference on Learning Theory, 2020

2019
Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing.
CoRR, 2019

2018
Dropout Training, Data-dependent Regularization, and Generalization Bounds.
Proceedings of the 35th International Conference on Machine Learning, 2018

Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints.
Proceedings of the Conference On Learning Theory, 2018

2017
Efficient Private ERM for Smooth Objectives.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Differentially Private Clustering in High-Dimensional Euclidean Spaces.
Proceedings of the 34th International Conference on Machine Learning, 2017

Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible.
Proceedings of the 34th International Conference on Machine Learning, 2017

A Refined Analysis of LSH for Well-dispersed Data Points.
Proceedings of the Fourteenth Workshop on Analytic Algorithmics and Combinatorics, 2017

2016
Stable Memory Allocation in the Hippocampus: Fundamental Limits and Neural Realization.
CoRR, 2016

2015
Politicize and Depoliticize: A Study of Semantic Shifts on People's Daily Fifty Years' Corpus via Distributed Word Representation Space.
Proceedings of the Chinese Lexical Semantics - 16th Workshop, 2015


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