Talks

  • Nonconvex Nonconcave Minimax Optimization for Data-driven Decision Making
    • INFORMS Annual Meeting, October, 2023 [slides].
  • Unifying Distributionally Robust Optimization via Optimal Transport Theory
    • International Conference Stochastic Programming, July, 2023 [slides].
  • Nonsmooth Nonconvex Nonconcave Minimax Optimization
    • NeurIPS 2022 Workshop on Optimization for Machine Learning, December, 2022 [slides].
    • International Conference on Continuous Optimization (ICCOPT), July, 2022 [slides].
    • Department of Mathematics, Rensselaer Polytechnic Institute, February, 2023.
  • Trade-off among Infeasibility, Efficiency and Accuracy for Gromov-Wasserstein Computation
    • SIAM Conference on Optimization (OP23), June 2023 [slides].
  • Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints [slides]
    • INFORMS Annual Meeting, October, 2022.
    • UT Austin EECS Rising Stars Workshop, October, 2022.
  • Modified Frank-Wolfe in Probability Space [slides]
    • Workshop “Robustness and Resilience in Stochastic Optimization and Statistical Learning: Mathematical Foundations”, May, 2022.
    • VinAI NeurIPS 2021 Workshop, Nov, 2021.
  • Efficient and Provable Algorithms for Wasserstein Distributionally Robust Optimization in Machine Learning [slides]
    • INFORMS Anuual Meeting, October, 2021.
    • ETH AI Center Post-Doctoral Fellowship Symposium, March 2021.
  • Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust SVM
    • NeurIPS 2020 (Poster), December 2020.
  • A First-Order Algorithmic Framework for Distributionally Robust Logistic Regression
    • The 17th Chinese Workshop on Machine Learning and applications (MLA 2019).
    • NeurIPS 2019 (Poster), December 2019.
  • Policy Optimization with Second-Order Advantage Information
    • IJCAI 2018 (Poster), July 2018.