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    Chris Liaw

    Chris Liaw

    Postdoc at University of Toronto
    Email: cvliaw@cs.toronto.edu

    • Toronto, Canada
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    About Me

    Hi! I am a postdoc in the theory group at the University of Toronto. Previously, I was a PhD student at the Department of Computer Science at UBC, where I was fortunate to be advised by Nick Harvey. I am broadly interested in randomized algorithms, machine learning theory, and mechanism design.

    Selected Publications

    • Optimal anytime regret with two experts, FOCS 2020
      (with Nick Harvey, Ed Perkins, Sikander Randhawa)
    • The Vickrey Auction with a Single Duplicate Bidder Approximates the Optimal Revenue, EC 2019
      (with Hu Fu and Sikander Randhawa)
    • Nearly-tight sample complexity bounds for learning mixtures of Gaussians via compression schemes, best paper at NeurIPS 2018
      (with Hassan Ashtiani, Shai Ben-David, Nick Harvey, Abbas Mehrabian, Yaniv Plan)
    • Nearly-tight VC-dimension bounds for piecewise linear neural networks, COLT 2017
      (with Peter L. Bartlett, Nick Harvey, Abbas Mehrabian)
    • A simple tool for bounding the deviation of random matrices on geometric sets, in Geometric Aspects of Functional Analysis
      (with Abbas Mehrabian, Yaniv Plan, and Roman Vershynin)
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