{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T04:18:47Z","timestamp":1780633127644,"version":"3.54.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:p>Many decision-making processes involve solving a combinatorial optimization problem with uncertain input that can be estimated from historic data. Recently, problems in this class have been successfully addressed via end-to-end learning approaches, which rely on solving one optimization problem for each training instance at every epoch. In this context, we provide two distinct contributions. First, we use a Noise Contrastive approach to motivate a family of surrogate loss functions, based on viewing non-optimal solutions as negative examples. Second, we address a major bottleneck of all predict-and-optimize approaches, i.e. the need to frequently recompute optimal solutions at training time. This is done via a solver-agnostic solution caching scheme, and by replacing optimization calls with a lookup in the solution cache. The method is formally based on an inner approximation of the feasible space and, combined with a cache lookup strategy, provides a controllable trade-off between training time and accuracy of the loss approximation. We empirically show that even a very slow growth rate is enough to match the quality of state-of-the-art methods, at a fraction of the computational cost.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/390","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"2833-2840","source":"Crossref","is-referenced-by-count":18,"title":["Contrastive Losses and Solution Caching for Predict-and-Optimize"],"prefix":"10.24963","author":[{"given":"Maxime","family":"Mulamba","sequence":"first","affiliation":[{"name":"Data Analytics Laboratory, Vrije Universiteit Brussel, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jayanta","family":"Mandi","sequence":"additional","affiliation":[{"name":"Data Analytics Laboratory, Vrije Universiteit Brussel, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michelangelo","family":"Diligenti","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematical Sciences, University of Siena, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michele","family":"Lombardi","sequence":"additional","affiliation":[{"name":"Dipartimento di Informatica - Scienza e Ingegneria, University of Bologna, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Victor","family":"Bucarey","sequence":"additional","affiliation":[{"name":"Data Analytics Laboratory, Vrije Universiteit Brussel, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tias","family":"Guns","sequence":"additional","affiliation":[{"name":"Data Analytics Laboratory, Vrije Universiteit Brussel, Belgium"},{"name":"Department of Computer Science, KU Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","theme":"Artificial Intelligence","location":"Montreal, Canada","acronym":"IJCAI-2021","number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2021,8,19]]},"end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:03:01Z","timestamp":1628679781000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/390"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/390","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}