{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:35:18Z","timestamp":1723016118514},"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>Bucket Elimination (BE) is a universal inference scheme that can solve most tasks over probabilistic and deterministic graphical models exactly.\n\nHowever, it often requires exponentially high levels of memory (in the induced-width) preventing its execution. In the spirit of exploiting Deep Learning for inference tasks, in this paper, we will use neural networks to approximate BE.\n\nThe resulting Deep Bucket Elimination (DBE) algorithm is developed for computing the partition function.\n\nWe provide a proof-of-concept empirically using instances from several different benchmarks, showing that DBE can be a more accurate approximation than current state-of-the-art approaches for approximating  BE (e.g. the mini-bucket schemes), especially when problems are sufficiently hard.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/582","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"4235-4242","source":"Crossref","is-referenced-by-count":1,"title":["Deep Bucket Elimination"],"prefix":"10.24963","author":[{"given":"Yasaman","family":"Razeghi","sequence":"first","affiliation":[{"name":"University of California, Irvine"}]},{"given":"Kalev","family":"Kask","sequence":"additional","affiliation":[{"name":"University of California, Irvine"}]},{"given":"Yadong","family":"Lu","sequence":"additional","affiliation":[{"name":"University of California, Irvine"}]},{"given":"Pierre","family":"Baldi","sequence":"additional","affiliation":[{"name":"University of California, Irvine"}]},{"given":"Sakshi","family":"Agarwal","sequence":"additional","affiliation":[{"name":"University of California, Irvine"}]},{"given":"Rina","family":"Dechter","sequence":"additional","affiliation":[{"name":"University of California, Irvine"}]}],"member":"10584","event":{"number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2021","name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","start":{"date-parts":[[2021,8,19]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","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":"2021-08-11T11:04:10Z","timestamp":1628679850000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/582"}},"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\/582","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}