Inverse Optimization with Fenchel-Young Losses: Regret Bounds and the Role of Geometry
arXiv:2502.16120v3 Announce Type: replace-cross
Abstract: Data-driven inverse optimization estimates unknown parameters of an optimization model from noisy and possibly suboptimal decision observations, with applications spanning logistics, portfolio …