Jie Wang

Variable Selection for Kernel Two-Sample Tests

  • Jie Wang
  • Santanu S. Dey
  • Yao Xie
    • Categories (Mixed) Integer Nonlinear Programming, Optimization in Data Science Tags , ,

    We consider the variable selection problem for two-sample tests, aiming to select the most informative features to best distinguish samples from two groups. We propose a kernel maximum mean discrepancy (MMD) framework to solve this problem and further derive its equivalent mixed-integer programming formulations for linear, quadratic, and Gaussian types of kernel functions. Our proposed … Read more

    Sinkhorn Distributionally Robust Optimization

  • Jie Wang
  • Rui Gao
  • Yao Xie
    • Categories Infinite Dimensional Optimization, Robust Optimization, Stochastic Programming

    We study distributionally robust optimization (DRO) with Sinkhorn distance—a variant of Wasserstein distance based on entropic regularization. We provide convex programming dual reformulation for a general nominal distribution. Compared with Wasserstein DRO, it is computationally tractable for a larger class of loss functions, and its worst-case distribution is more reasonable. We propose an efficient first-order … Read more