• Recent Progresses on the Theory of Multi-Agent Reinforcement Learning and Games.
    Guest Lecture at CS332, Stanford University, Oct 2022.

  • Near-Optimal Learning of Extensive-Form Games with Imperfect Information.
    Learning and Games Program, Simons Institute, April 2022.
    CISS Conference, Princeton University, March 2022.

  • Understanding the Under-Coverage Bias in Uncertainty Estimation.
    Statistics Department Seminar, Rutgers University, October 2021.

  • Provable Self-Play Algorithms for Competitive Reinforcement Learning.
    Facebook AI Research, March 2020.

  • ProxQuant: Quantized Neural Networks via Proximal Operators
    Bytedance AI Lab, Dec 2018, Menlo Park, CA.
    Amazon AI, Sep 2018, East Palo Alto, CA.

  • On the Generalization and Approximation in Generative Adversarial Networks (GANs)
    Google Brain, Nov 2018, Mountain View, CA.
    Salesforce Research, Nov 2018, Palo Alto, CA.
    Stanford ML Seminar, Oct 2018, Stanford, CA.

  • Optimization Landscape of some Non-convex Learning Problems
    Stanford Theory Seminar, Apr 2018, Stanford, CA.
    Stanford ML Seminar, Apr 2017, Stanford, CA.