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Author Information
Jialei Wang (University of Chicago)
Mladen Kolar (University of Chicago)
Nati Srebro (Toyota Technological Institute at Chicago)
Tong Zhang (HKUST)

Tong Zhang is a professor of Computer Science and Mathematics at the Hong Kong University of Science and Technology. His research interests are machine learning, big data and their applications. He obtained a BA in Mathematics and Computer Science from Cornell University, and a PhD in Computer Science from Stanford University. Before joining HKUST, Tong Zhang was a professor at Rutgers University, and worked previously at IBM, Yahoo as research scientists, Baidu as the director of Big Data Lab, and Tencent as the founding director of AI Lab. Tong Zhang was an ASA fellow and IMS fellow, and has served as the chair or area-chair in major machine learning conferences such as NIPS, ICML, and COLT, and has served as associate editors in top machine learning journals such as PAMI, JMLR, and Machine Learning Journal.
Related Events (a corresponding poster, oral, or spotlight)
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2017 Poster: Efficient Distributed Learning with Sparsity »
Tue. Aug 8th 08:30 AM -- 12:00 PM Room Gallery #119
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2021 : Efficient Exploration by HyperDQN in Deep Reinforcement Learning »
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2022 Poster: Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets »
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2022 Poster: Sparse Invariant Risk Minimization »
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2021 Poster: Fast margin maximization via dual acceleration »
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2021 Poster: Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels »
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2021 Poster: On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent »
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2019 Poster: Semi-Cyclic Stochastic Gradient Descent »
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2019 Oral: Semi-Cyclic Stochastic Gradient Descent »
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