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Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learning
Our experiments show that by using SFGE we can: (1) deal with predictions that occur both in the objective function and in the constraints; and (2) effectively tackle two-stage stochastic optimization problems.
UNIFY: a Unified Policy Designing Framework for Solving Constrained Optimization Problems with Machine Learning
Our approach relies on a clever decomposition of the policy in two stages, namely an unconstrained ML model and a CO problem, to take advantage of the strength of each approach while compensating for its weaknesses.
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