{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T20:31:32Z","timestamp":1774557092001,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031496134","type":"print"},{"value":"9783031496141","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,12,9]],"date-time":"2023-12-09T00:00:00Z","timestamp":1702080000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,9]],"date-time":"2023-12-09T00:00:00Z","timestamp":1702080000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-49614-1_1","type":"book-chapter","created":{"date-parts":[[2023,12,8]],"date-time":"2023-12-08T14:02:45Z","timestamp":1702044165000},"page":"3-15","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Differentiable Discrete Optimization Using Dataless Neural Networks"],"prefix":"10.1007","author":[{"given":"Sangram K.","family":"Jena","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K.","family":"Subramani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alvaro","family":"Velasquez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,9]]},"reference":[{"key":"1_CR1","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.tcs.2015.09.023","volume":"609","author":"T Akiba","year":"2016","unstructured":"Akiba, T., Iwata, Y.: Branch-and-reduce exponential\/FPT algorithms in practice: a case study of vertex cover. Theoret. Comput. Sci. 609, 211\u2013225 (2016)","journal-title":"Theoret. Comput. Sci."},{"key":"1_CR2","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1016\/j.neunet.2022.08.008","volume":"155","author":"IR Alkhouri","year":"2022","unstructured":"Alkhouri, I.R., Atia, G.K., Velasquez, A.: A differentiable approach to the maximum independent set problem using dataless neural networks. Neural Netw. 155, 168\u2013176 (2022)","journal-title":"Neural Netw."},{"issue":"2","key":"1_CR3","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1016\/j.ejor.2020.07.063","volume":"290","author":"Y Bengio","year":"2021","unstructured":"Bengio, Y., Lodi, A., Prouvost, A.: Machine learning for combinatorial optimization: a methodological tour d\u2019horizon. Eur. J. Oper. Res. 290(2), 405\u2013421 (2021)","journal-title":"Eur. J. Oper. Res."},{"issue":"2","key":"1_CR4","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1007\/BF01994876","volume":"32","author":"R Boppana","year":"1992","unstructured":"Boppana, R., Halld\u00f3rsson, M.M.: Approximating maximum independent sets by excluding subgraphs. BIT Numer. Math. 32(2), 180\u2013196 (1992)","journal-title":"BIT Numer. Math."},{"key":"1_CR5","doi-asserted-by":"publisher","unstructured":"Cygan, M., et al.: Parameterized Algorithms. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-21275-3","DOI":"10.1007\/978-3-319-21275-3"},{"key":"1_CR6","doi-asserted-by":"crossref","unstructured":"Drori, I., et al.: Learning to solve combinatorial optimization problems on real-world graphs in linear time. In: 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 19\u201324 (2020)","DOI":"10.1109\/ICMLA51294.2020.00013"},{"key":"1_CR7","doi-asserted-by":"crossref","unstructured":"Festa, P.: A brief introduction to exact, approximation, and heuristic algorithms for solving hard combinatorial optimization problems. In: 2014 16th International Conference on Transparent Optical Networks (ICTON), pp. 1\u201320 (2014)","DOI":"10.1109\/ICTON.2014.6876285"},{"key":"1_CR8","series-title":"Texts in Theoretical Computer Science. An EATCS Series","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-29953-X","volume-title":"Parameterized Complexity Theory","author":"J Flum","year":"2006","unstructured":"Flum, J., Grohe, M.: Parameterized Complexity Theory. TTCSAES, Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/3-540-29953-X"},{"key":"1_CR9","series-title":"Texts in Theoretical Computer Science. An EATCS Series","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-16533-7","volume-title":"Exact Exponential Algorithms","author":"FV Fomin","year":"2010","unstructured":"Fomin, F.V., Kratsch, D.: Exact Exponential Algorithms. TTCSAES, Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-16533-7"},{"key":"1_CR10","unstructured":"Gaspers, S.: Exponential Time Algorithms - Structures, Measures, and Bounds. VDM (2010)"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Lamm, S., Sanders, P., Schulz, C., Strash, D., Werneck, R.F.: Finding near-optimal independent sets at scale. In: 2016 Proceedings of the Eighteenth Workshop on Algorithm Engineering and Experiments (ALENEX), pp. 138\u2013150 (2016)","DOI":"10.1137\/1.9781611974317.12"},{"key":"1_CR12","unstructured":"Li, Z., Chen, Q., Koltun, V.: Combinatorial optimization with graph convolutional networks and guided tree search. In: Advances in Neural Information Processing Systems, vol. 31 (2018)"},{"key":"1_CR13","doi-asserted-by":"publisher","first-page":"105400","DOI":"10.1016\/j.cor.2021.105400","volume":"134","author":"N Mazyavkina","year":"2021","unstructured":"Mazyavkina, N., Sviridov, S., Ivanov, S., Burnaev, E.: Reinforcement learning for combinatorial optimization: a survey. Comput. Oper. Res. 134, 105400 (2021)","journal-title":"Comput. Oper. Res."},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Niedermeier, R.: Invitation to Fixed-Parameter Algorithms. Oxford University Press (2006)","DOI":"10.1093\/acprof:oso\/9780198566076.001.0001"},{"issue":"2","key":"1_CR15","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1016\/j.cor.2010.07.019","volume":"38","author":"PS Segundo","year":"2011","unstructured":"Segundo, P.S., Rodr\u00edguez-Losada, D., Jim\u00e9nez, A.: An exact bit-parallel algorithm for the maximum clique problem. Comput. Oper. Res. 38(2), 571\u2013581 (2011)","journal-title":"Comput. Oper. Res."},{"issue":"4","key":"1_CR16","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1038\/s42256-022-00468-6","volume":"4","author":"MJA Schuetz","year":"2022","unstructured":"Schuetz, M.J.A., Brubaker, J.K., Katzgraber, H.G.: Combinatorial optimization with physics-inspired graph neural networks. Nat. Mach. Intell. 4(4), 367\u2013377 (2022)","journal-title":"Nat. Mach. Intell."},{"key":"1_CR17","doi-asserted-by":"crossref","unstructured":"Wilder, B., Dilkina, B., Tambe, M.: Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 1658\u20131665 (2019)","DOI":"10.1609\/aaai.v33i01.33011658"}],"container-title":["Lecture Notes in Computer Science","Combinatorial Optimization and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-49614-1_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,10]],"date-time":"2024-02-10T09:02:36Z","timestamp":1707555756000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-49614-1_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,9]]},"ISBN":["9783031496134","9783031496141"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-49614-1_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,9]]},"assertion":[{"value":"9 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"COCOA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Combinatorial Optimization and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hawai, HI","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cocoa2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/theory.utdallas.edu\/COCOA2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EquinOCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"117","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"73","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"62% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}