Difan Zou

Department of Computer Science

University of California, Los Angeles

Contact: knowzou+ at + ucla.edu

404 Westwood Plaza

Engineering VI

Los Angeles, CA 90095-1596

I am currently a PhD student at the Department of Computer Science, University of California, Los Angeles. My research interests lie in the theoretical understanding of machine learning and deep learning problems.

My advisor is Prof. Quanquan Gu since 2017. Previously I was working with Prof. Chen Gong and Prof. Zhengyuan Xu in optical wireless communication and networking center in USTC.

I am really excited to receive the 2020/21 Bloomberg Data Science Ph.D. Fellowship!

Education

  • B.S. University of Science and Technology of China (Applied Physics, School of Gifted Young) 2010-2014

  • M.S. University of Science and Technology of China (Electrical Engineering and Information Science) 2014-2017

  • Ph.D. University of Virginia (System and Information Engineering) 2017-2018

  • Ph.D. University of California, Los Angeles (Computer Science) 2018-present

Project

Publication

(* indicates equal contribution )

Preprint

Yaodong Yu*, Difan Zou*, Quanquan Gu.

Difan Zou, Lingxiao Wang, Pan Xu, Jinghui Chen, Weitong Zhang and Quanquan Gu.

Conference & Journal

Difan Zou*, Jingfeng Wu*, Vladimir Braverman, Quanquan Gu and Sham Kakade

Difan Zou, Pan Xu and Quanquan Gu

Difan Zou, Quanquan Gu

Difan Zou*, Spencer Frei* and Quanquan Gu

Zixiang Chen*, Yuan Cao*, Difan Zou* and Quanquan Gu.

Jingfeng Wu, Difan Zou, Vladimir Braverman and Quanquan Gu

Bao Wang*, Difan Zou*, Quanquan Gu, Stanley Osher.

Difan Zou, Philip M. Long and Quanquan Gu

Yisen Wang*, Difan Zou*, Jinfeng Yi, James Bailey, Xingjun Ma and Quanquan Gu

Difan Zou*, Yuan Cao*, Dongruo Zhou, Quanquan Gu

Difan Zou, Quanquan Gu

Difan Zou*, Ziniu Hu*, Yewen Wang, Song Jiang, Yizhou Sun, Quanquan Gu

Difan Zou, Pan Xu, Quanquan Gu

Difan Zou, Pan Xu, Quanquan Gu

  • Global convergence of Langevin dynamics based algorithms for nonconvex optimization (Neural Information Processing System (NeurIPS'18))

Pan Xu*, Jinghui Chen*, Difan Zou, Quanquan Gu

  • Subsampled stochastic variance-reduced gradient Langevin dynamics ( International Conference on Uncertainty in Artificial Intelligence (UAI'18))

Difan Zou*, Pan Xu*, Quanquan Gu

  • Stochastic Variance-Reduced Hamilton Monte Carlo Methods (International Conference on Machine Learning (ICML'18))

Difan Zou*, Pan Xu*, Quanquan Gu


Teaching

  • CS 180: Algorithm and Complexity (Spring 2020, UCLA)

  • CS M146: Machine Learning (Winter 2020, UCLA)

  • SYS 2202: Data and Information Engineering (Spring 2018, UVa)

  • SYS 6018: Data Mining (Spring 2018, UVa)

  • CS6501: Optimization (Fall 2017, UVa)

  • SYS6501: Statistic Modeling (Fall 2017, UVa)