{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T23:04:37Z","timestamp":1726095877191},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030584740"},{"type":"electronic","value":"9783030584757"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-58475-7_51","type":"book-chapter","created":{"date-parts":[[2020,9,6]],"date-time":"2020-09-06T20:02:35Z","timestamp":1599422555000},"page":"885-898","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Learning the Satisfiability of Pseudo-Boolean Problem with Graph Neural Networks"],"prefix":"10.1007","author":[{"given":"Minghao","family":"Liu","sequence":"first","affiliation":[]},{"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Pei","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Shuzi","family":"Niu","sequence":"additional","affiliation":[]},{"given":"Feifei","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,2]]},"reference":[{"key":"51_CR1","unstructured":"Amizadeh, S., Matusevych, S., Weimer, M.: Learning to solve circuit-SAT: an unsupervised differentiable approach. In: 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA (2019)"},{"key":"51_CR2","unstructured":"Amizadeh, S., Matusevych, S., Weimer, M.: PDP: a general neural framework for learning constraint satisfaction solvers. arXiv preprint arXiv:1903.01969 (2019)"},{"key":"51_CR3","unstructured":"Balunovic, M., Bielik, P., Vechev, M.T.: Learning to solve SMT formulas. In: Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems, NeurIPS 2018, Montr\u00e9al, Canada, pp. 10338\u201310349 (2018)"},{"key":"51_CR4","unstructured":"Bello, I., Pham, H., Le, Q.V., Norouzi, M., Bengio, S.: Neural combinatorial optimization with reinforcement learning. In: 5th International Conference on Learning Representations, ICLR 2017, Workshop Track Proceedings, Toulon, France (2017)"},{"key":"51_CR5","doi-asserted-by":"crossref","unstructured":"Cameron, C., Chen, R., Hartford, J.S., Leyton-Brown, K.: Predicting propositional satisfiability via end-to-end learning. The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, NY, USA, New York, pp. 3324\u20133331 (2020)","DOI":"10.1609\/aaai.v34i04.5733"},{"key":"51_CR6","doi-asserted-by":"crossref","unstructured":"Elffers, J., Nordstr\u00f6m, J.: Divide and conquer: towards faster pseudo-Boolean solving. In: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, Stockholm, Sweden, pp. 1291\u20131299 (2018)","DOI":"10.24963\/ijcai.2018\/180"},{"issue":"1","key":"51_CR7","first-page":"17","volume":"5","author":"P Erd\u0151s","year":"1960","unstructured":"Erd\u0151s, P., R\u00e9nyi, A.: On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci 5(1), 17\u201360 (1960)","journal-title":"Publ. Math. Inst. Hung. Acad. Sci"},{"key":"51_CR8","volume-title":"Linear programming: methods and applications","author":"SI Gass","year":"2003","unstructured":"Gass, S.I.: Linear programming: methods and applications. Courier Corporation, North Chelmsford (2003)"},{"key":"51_CR9","unstructured":"Gilmer, J., Schoenholz, S.S., Riley, P.F., Vinyals, O., Dahl, G.E.: Neural message passing for quantum chemistry. In: Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, pp. 1263\u20131272 (2017)"},{"issue":"3","key":"51_CR10","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/BF00339943","volume":"52","author":"JJ Hopfield","year":"1985","unstructured":"Hopfield, J.J., Tank, D.W.: Neural computation of decisions in optimization problems. Biol. Cybern. 52(3), 141\u2013152 (1985)","journal-title":"Biol. Cybern."},{"key":"51_CR11","volume-title":"Pseudo-Boolean Programming and Applications: Presented at the Colloquium on Mathematics and Cybernetics in the Economy","author":"PL Ivanescu","year":"2006","unstructured":"Ivanescu, P.L.: Pseudo-Boolean Programming and Applications: Presented at the Colloquium on Mathematics and Cybernetics in the Economy, vol. 9. Springer, Berlin (2006)"},{"key":"51_CR12","doi-asserted-by":"publisher","unstructured":"Karp, R.M.: Reducibility among combinatorial problems. In: Proceedings of a Symposium on the Complexity of Computer Computations, New York, USA, pp. 85\u2013103 (1972). https:\/\/doi.org\/10.1007\/978-1-4684-2001-2_9","DOI":"10.1007\/978-1-4684-2001-2_9"},{"key":"51_CR13","unstructured":"Khalil, E.B., Dai, H., Zhang, Y., Dilkina, B., Song, L.: Learning combinatorial optimization algorithms over graphs. In: Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems, NIPS 2017, Long Beach, CA, USA, pp. 6348\u20136358 (2017)"},{"key":"51_CR14","doi-asserted-by":"crossref","unstructured":"Khalil, E.B., Dilkina, B., Nemhauser, G.L., Ahmed, S., Shao, Y.: Learning to run heuristics in tree search. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, pp. 659\u2013666 (2017)","DOI":"10.24963\/ijcai.2017\/92"},{"issue":"7553","key":"51_CR15","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436 (2015)","journal-title":"Nature"},{"key":"51_CR16","doi-asserted-by":"crossref","unstructured":"Lemos, H., Prates, M.O.R., Avelar, P.H.C., Lamb, L.C.: Graph colouring meets deep learning: effective graph neural network models for combinatorial problems. In: 31st IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2019, Portland, OR, USA, pp. 879\u2013885 (2019)","DOI":"10.1109\/ICTAI.2019.00125"},{"key":"51_CR17","unstructured":"Li, Z., Chen, Q., Koltun, V.: Combinatorial optimization with graph convolutional networks and guided tree search. Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, Montr\u00e9al, Canada, pp. 537\u2013546 (2018)"},{"key":"51_CR18","doi-asserted-by":"crossref","unstructured":"Milan, A., Rezatofighi, S.H., Garg, R., Dick, A.R., Reid, I.D.: Data-driven approximations to NP-hard problems. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, California, USA, pp. 1453\u20131459 (2017)","DOI":"10.1609\/aaai.v31i1.10750"},{"issue":"4","key":"51_CR19","doi-asserted-by":"publisher","first-page":"570","DOI":"10.1287\/opre.47.4.570","volume":"47","author":"D Pisinger","year":"1999","unstructured":"Pisinger, D.: Core problems in knapsack algorithms. Oper. Res. 47(4), 570\u2013575 (1999)","journal-title":"Oper. Res."},{"key":"51_CR20","doi-asserted-by":"crossref","unstructured":"Prates, M.O.R., Avelar, P.H.C., Lemos, H., Lamb, L.C., Vardi, M.Y.: Learning to solve NP-complete problems: a graph neural network for decision TSP. In: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, Honolulu, Hawaii, USA, pp. 4731\u20134738 (2019)","DOI":"10.1609\/aaai.v33i01.33014731"},{"key":"51_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1007\/978-3-030-24258-9_24","volume-title":"Theory and Applications of Satisfiability Testing \u2013 SAT 2019","author":"D Selsam","year":"2019","unstructured":"Selsam, D., Bj\u00f8rner, N.: Guiding high-performance SAT solvers with Unsat-Core predictions. In: Janota, M., Lynce, I. (eds.) SAT 2019. LNCS, vol. 11628, pp. 336\u2013353. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-24258-9_24"},{"key":"51_CR22","unstructured":"Selsam, D., Lamm, M., B\u00fcnz, B., Liang, P., de Moura, L., Dill, D.L.: Learning a SAT solver from single-bit supervision. In: 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA (2019)"},{"key":"51_CR23","unstructured":"Vinyals, O., Fortunato, M., Jaitly, N.: Pointer networks. Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems, NIPS 2015, Montreal, Quebec, Canada, pp. 2692\u20132700 (2015)"},{"key":"51_CR24","series-title":"International series in operations research & management science","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-92280-5","volume-title":"Logic and Integer Programming","author":"HP Williams","year":"2009","unstructured":"Williams, H.P.: Logic and Integer Programming. ISORMS, vol. 130. Springer, Boston, MA (2009). https:\/\/doi.org\/10.1007\/978-0-387-92280-5"},{"key":"51_CR25","volume-title":"Integer and Combinatorial Optimization","author":"LA Wolsey","year":"2014","unstructured":"Wolsey, L.A., Nemhauser, G.L.: Integer and Combinatorial Optimization. John Wiley & Sons, Hoboken (2014)"},{"key":"51_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1007\/978-3-319-98334-9_38","volume-title":"Principles and Practice of Constraint Programming","author":"H Xu","year":"2018","unstructured":"Xu, H., Koenig, S., Kumar, T.K.S.: Towards effective deep learning for constraint satisfaction problems. In: Hooker, J. (ed.) CP 2018. LNCS, vol. 11008, pp. 588\u2013597. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98334-9_38"},{"key":"51_CR27","unstructured":"Zhou, J., et al.: Graph neural networks: a review of methods and applications. arXiv preprint arXiv:1812.08434 (2018)"}],"container-title":["Lecture Notes in Computer Science","Principles and Practice of Constraint Programming"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58475-7_51","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,16]],"date-time":"2022-11-16T22:53:36Z","timestamp":1668639216000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58475-7_51"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030584740","9783030584757"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58475-7_51","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"2 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Principles and Practice of Constraint Programming","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Louvain-la-Neuve","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Belgium","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cp2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cp2020.a4cp.org\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"122","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":"55","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":"45% - 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":"3.13","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":"3.47","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)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}