1 citations · 1 across the 4 of their papers we have counts for
4 papers
The Signed Wasserstein Barycenter Problem
Matt Jacobs, Bohan Zhou
Barycenter problems encode important geometric information about a metric space. While these problems are typically studied with positive weight coefficients associated to each dis…
Guaranteeing Higher Order Convergence Rates for Accelerated Wasserstein Gradient Flow Schemes
Raymond Chu, Matt Jacobs
In this paper, we study higher-order-accurate-in-time minimizing movements schemes for Wasserstein gradient flows. We introduce a novel accelerated second-order scheme, leveraging…
Asymptotic Linear Convergence of ADMM for Isotropic TV Norm Compressed Sensing
Emmanuel Gil Torres, Matt Jacobs, Xiangxiong Zhang
We prove an explicit local linear rate for ADMM solving the isotropic Total Variation (TV) norm compressed sensing problem in multiple dimensions, by analyzing the auxiliary variab…
An Optimal Transport Approach for Computing Adversarial Training Lower Bounds in Multiclass Classification
Nicolas Garcia Trillos, Matt Jacobs, Jakwang Kim +1
Despite the success of deep learning-based algorithms, it is widely known that neural networks may fail to be robust. A popular paradigm to enforce robustness is adversarial traini…