Adam N. Elmachtoub, Tianyi Lin, Wenxuan Liu · 2026 · arXiv
DOI: 10.48550/arXiv.2610.29918 · open-access PDF
एक संदर्भ रेखात्मक अनुकूलन समस्या पर विचार करें, जहां एक पूर्वानुमान-तब-अनुकूलन (पीटीओ) प्रणाली अपने नीचे की रेखात्मक प्रोग्राम में उपयोग किए जाने वाले लागत वेक्टरों को प्रकट किए बिना इष्टतम निर्णयों को वापस करती है। हमारा ध्यान इस पर केंद्रित है कि हमलावरों, जो संदर्भ पूछताछ भेज सकते हैं, को आधारित पूर्वानुमान मॉडल को निकालने से कैसे रोकें।
Machine translation (Meta M2M100); the English original follows.
Consider a contextual linear optimization problem, where a predict-then-optimize (PTO) system returns optimal decisions without revealing the cost vectors used in its downstream linear program. Our focus is on how to prevent attackers, who can submit context queries, from extracting the underlying prediction model. Although the cost-to-decision map is many-to-one, observations across contexts can reveal the underlying prediction model. For linear models, we provide sufficient conditions where the attacker can learn the model up to positive scaling by only observing the decision. These conditio
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