From Inverse Optimization to Feasibility to ERM

arXiv:2402.17890v1 Announce Type: new
Abstract: Inverse optimization involves inferring unknown parameters of an optimization problem from known solutions, and is widely used in fields such as transportation, power systems and healthcare. We study the contextual inverse optimization setting that utilizes additional contextual information to better predict the unknown problem parameters. We focus on contextual inverse linear programming (CILP), addressing the challenges posed by the non-differentiable nature of LPs. For a linear prediction model, we reduce CILP to a convex feasibility …

abstract arxiv cs.lg erm fields focus healthcare information math.oc optimization parameters power solutions study systems transportation type