A latent-variable hypothesis class lets inverse optimization recover feasible regions for known linear objectives, with convex and MILP training reformulations in special cases.
Inverse optimization for assessing emerging technologies in breast cancer screening
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Inverse Optimization via Learning Feasible Regions
A latent-variable hypothesis class lets inverse optimization recover feasible regions for known linear objectives, with convex and MILP training reformulations in special cases.