Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:	Dr. Xiaojing Ye，Georgia State University
Inviter:	陈冲博士
Title:	Learning to Match: An Inverse Optimal Transport Approach
Time & Venue:	2019.5.28 15:00-16:00 N202
Abstract:	We propose a unified data-driven framework based on inverse optimal transport that can learn adaptive, nonlinear interaction cost function from noisy and incomplete empirical matching matrix and predict new matching in various matching contexts. We emphasize that the discrete optimal transport plays the role of a variational principle which gives rise to an optimization based framework for modeling the observed empirical matching data. Our formulation leads to a bi-level non-convexoptimization problem, for which we develop an efficient algorithm based on a saddle-point formulation of the optimization problem. The proposed approach has wide applicability including predicting matching in online dating, labor market, college application and crowdsourcing. We back up our claims with numerical experiments on both synthetic data and real world data sets.