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cs.LG2026
Scalable Decision-Focused Learning through Cost-Sensitive Regression
Noah Schutte, Senne Berden, Tias Guns +2
Many real-world combinatorial problems involve uncertain parameters, which can be predicted given contextual features and historical data. These `predict-then-optimize' or `context…
cs.LG2026
Sufficient Decision Proxies for Decision-Focused Learning
Noah Schutte, Grigorii Veviurko, Krzysztof Postek +1
When solving optimization problems under uncertainty with contextual data, utilizing machine learning to predict the uncertain parameters' values is a popular and effective approac…
cs.LG2024
Robust Losses for Decision-Focused Learning
Noah Schutte, Krzysztof Postek, Neil Yorke-Smith
Optimization models used to make discrete decisions often contain uncertain parameters that are context-dependent and estimated through prediction. To account for the quality of th…