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Liwei Wang

Professor,

Department of Machine Intelligence,

School of Electronics Engineering and Computer Sciences,

Peking University

Email: wanglw at pku.edu.cn; wanglw at cis.pku.edu.cn


My main research interest is machine learning. I study learning theory, providing insights for the strength and weakness of existing learning algorithms and thus help to guide the development of new algorithms. I am also interested in differential privacy, especially in design learning algorithms with privacy guarantees. On the application side, I develop algorithms and systems for medical diagnosis based on machine learning methods.



NEWS



  • Our paper: "To What Extent Do Different Neural Networks Learn the Same Representation: A Neuron Activation Subspace Match Approach" by Liwei Wang ,Lunjia Hu, Jiayuan Gu, Zhiqiang Hu, Yue Wu, Kun He, John Hopcroft has been accepted by NIPS 2018!
  • Our paper: "FRAGE: Frequency-Agnostic Word Representation" by Chengyue Gong,Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu has been accepted by NIPS 2018!
  • Our paper: "Learning to Navigate for Fine-grained Classification" by Ze Yang, Tiange Luo, Dong Wang, Zhiqiang Hu, Jun Gao, Liwei Wang has been accepted by ECCV 2018!
  • Our paper: "Learning Region Features for Object Detection" by Jiayuan Gu, Han Hu, Liwei Wang, Yichen Wei, Jifeng Dai has been accepted by ECCV 2018!
  • Our paper: "Dropout Training, Data-dependent Regularization, and Generalization Bounds" by Wenlong Mou, Yuchen Zhou, Jun Gao, Liwei Wang has been accepted by ICML 2018!
  • Our paper: "Towards Binary-Valued Gates for Robust LSTM Training" by Di He, Zhuohan Li, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tieyan Liu has been accepted by ICML 2018!
  • Our paper: "Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints" by Wenlong Mou, Liwei Wang, Xiyu Zhai, Kai Zheng has been accepted by COLT 2018!
  • Our team has achieved the 1st place in TianChi AI Competition for Healthcare (Season 1)!

RECENT PUBLICATIONS (Full Paper List)


Full publication list here


Open Source Codes




Students



Current Students

PhD Students Master Students Undergraduate Students
  • Xiaoyu Chen
  • Di He
  • Aoxue Li
  • Dong Wang
  • Kai Zheng
  • Yihong Chen
  • Yuting Dai
  • Tiange Luo
  • Yichuan Wang
  • Ze Yang
  • Kexin Zhang
  • TianLe Cai
  • Shengcao Cao
  • Siyu Chen
  • Dengbo Chen
  • Ruiqi Gao
  • Jiachen Hu
  • Haochuan Li
  • Jiawei Li
  • Zhuohan Li
  • Chuan Lin
  • Yiping Lu
  • Yijia Weng
  • Yue Wu
  • Jinchen Xuan
  • Yunchang Yang
  • Runtian Zhai
  • Shishuang Zhao


Postdoctoral

  • Ke Lin
Past Students

  • Yifan Chen (Caltech)
  • Yuxi Chen (Google)
  • Chen Dan (CMU)
  • Xiaocheng Deng (Micorsoft)
  • Jia Ding (Ant Financial)
  • Xialiang Dou (University of Chicago)
  • Kai Fan (Duke)
  • Jun Gao (University of Toronto)
  • Jiayuan Gu (UCSD)
  • Zhiqiang Hu (SenseTime)
  • Lunjia Hu (Stanford)
  • He Jiang (University of Southern California)
  • Chi Jin (UC Berkeley)
  • Zhaoxiang Jing (Chinese Academy of Sciences)
  • Yao Liu (Stanford)
  • Tianhong Li (MIT)
  • Yuhan Liu (Cornell University)
  • Zhou Lu (Princeton)
  • Wenlong Mou (UC Berkeley)
  • Hongming Pu (University of Pennsylvania)
  • Zihan Tan (University of Chicago)
  • Zhi Wang(Columbia University)
  • Ziteng Wang (Didi Research)
  • Feicheng Wang (Harvard University)
  • Chenwei Wu (Duke University)
  • Songbai Yan (UCSD)
  • Xuchen You (University of Maryland)
  • Hongyuan You (UCSB)
  • Xiyu Zhai (MIT)
  • Chicheng Zhang (Microsoft)
  • Hongyi Zhang (MIT)
  • Jiaqi Zhang (Ant Financial)
  • Yichen Zhang (NYU)
  • Mengxiao Zhang (University of Southern California)
  • Yiqiao Zhong (Princeton)
  • Yuchen Zhou (University of Wisconsin)
  • Xu Zou (Tsinghua University)

Courses



Current Courses

  • Machine Learning
  • Information Theory

Previous Courses

  • Statistical Learning