Wenlong Mou (牟文龙)

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PhD student,
Department of EECS,
UC Berkeley
Office: 264 Cory Hall, Berkeley, CA
Phone: +1 510 409 5625
E-mail: wmou [@] berkeley [DOT] edu

About me

I am a second-year Ph.D. student at Department of EECS, UC Berkeley. I'm very fortunate to be advised by Prof. Martin Wainwright and Prof. Peter Bartlett. Prior to Berkeley, I received B.S. in Computer Science from Peking University in 2017, where I was fortunate to work with Prof. Liwei Wang. In 2016, I spent a wonderful summer at CMU, working with Prof. Nina Balcan


My research interests are broadly in statistics, machine learning theory, optimization and applied probability. The goal of my research is to push the frontier of computational/statistical possibilities for big data analysis, under minimal assumptions. Currently, I'm particularly interested in the following topics:

  • Diffusion process and SDEs, High-dimensional sampling algorithm, Interplay betweenoptimization and sampling, Stein’s method and Poisson equation.

  • High-dimensional statistics, Learning theory, Localization and Oracle inequalities.

  • Statistical estimation problems with temporal dependence, inference with underlying Markov chains or martingale structure.

  • Optimization and sampling for statistical inference, Non-convex loss surfaces.

Find out more.

Recent Publications

  1. Wenglon Mou, Nicolas Flammarion, Martin Wainwright, Peter Bartlett, "Improved Bound for Discretization of Langevin Diffusion: Achieving Near-Optimal Rates without Convexity"

  2. Wenglon Mou, Nhat Ho, Martin Wainwright, Peter Bartlett, Michael Jordan, "Polynomial-time algorithm for power posterior sampling in Bayesian mixture models"

  3. Wenlong Mou, Liwei Wang, Xiyu Zhai, Kai Zheng, "Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints", In COLT 2018 (alphabetical order)

  4. Wenlong Mou, Yuchen Zhou, Jun Gao, Liwei Wang "Dropout Training, Data-dependent Regularization and Generalization Bounds ", In ICML 2018

  5. Maria-Florina Balcan, Travis Dick, Yingyu Liang, Wenlong Mou and Hongyang Zhang, "Differentially Private Clustering in High-dimensional Euclidean Space", In ICML 2017 (alphabetical order)

  6. Kai Zheng, Wenlong Mou (equal contribution), Liwei Wang, "Collect at Once, Use Effec-tively: Making Non-interactive Locally Private Learning Possible", In ICML 2017


I'm fortunate to have collaborated with following people (in reverse chronological order):
Tianyi Lin, Jiantao Jiao, Yian Ma, Nhat Ho, Nicolas Flammarion, Yuansi Chen, Raaz Dwivedi, Peter Bartlett, Martin Wainwright, Yuchen Zhou, Jun Gao, Xiyu Zhai, Hongyang Zhang, Yingyu Liang, Colin White, Travis Dick, Maria-Florina Balcan, Kai Zheng, Jiaqi Zhang, Zhi Wang, Liwei Wang