18 citations · 59 across the 19 of their papers we have counts for
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New Proximal Newton-Type Methods for Convex Optimization
Ilan Adler, Zhiyue Tom Hu, Tianyi Lin
In this paper, we propose new proximal Newton-type methods for convex optimization problems in composite form. The applications include model predictive control (MPC) and embedded…
On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
Tianyi Lin, Zeyu Zheng, Elynn Y. Chen +2
Optimal transport (OT) distances are increasingly used as loss functions for statistical inference, notably in the learning of generative models or supervised learning. Yet, the be…
Projection Robust Wasserstein Distance and Riemannian Optimization
Tianyi Lin, Chenyou Fan, Nhat Ho +2
Projection robust Wasserstein (PRW) distance, or Wasserstein projection pursuit (WPP), is a robust variant of the Wasserstein distance. Recent work suggests that this quantity is m…
Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm
Tianyi Lin, Nhat Ho, Xi Chen +2
We study the fixed-support Wasserstein barycenter problem (FS-WBP), which consists in computing the Wasserstein barycenter of discrete probability measures supported on a finit…