{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T10:28:18Z","timestamp":1743071298861,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030967710"},{"type":"electronic","value":"9783030967727"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-030-96772-7_41","type":"book-chapter","created":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T21:13:08Z","timestamp":1647378788000},"page":"452-459","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Approximating BP Maximization with\u00a0Distorted-Based Strategy"],"prefix":"10.1007","author":[{"given":"Ruiqi","family":"Yang","sequence":"first","affiliation":[]},{"given":"Suixiang","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Lu","family":"Han","sequence":"additional","affiliation":[]},{"given":"Gaidi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhongrui","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,3,16]]},"reference":[{"key":"41_CR1","doi-asserted-by":"crossref","unstructured":"Badanidiyuru, A., Mirzasoleiman, B., Karbasi, A., Krause, A.: Streaming submodular maximization: massive data summarization on the fly. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 671\u2013680 (2014)","DOI":"10.1145\/2623330.2623637"},{"key":"41_CR2","unstructured":"Bai, W., Bilmes, J.: Greed is still good: maximizing monotone submodular+supermodular (BP) functions. In: Proceedings of the 35th International Conference on Machine Learning, vol. 80, pp. 304\u2013313 (2018)"},{"key":"41_CR3","unstructured":"Bogunovic, I., Mitrovi\u0107, S., Scarlett, J., Cevher, V.: Robust submodular maximization: a non-uniform partitioning approach. In: Proceedings of the 34th International Conference on Machine Learning, vol. 70, pp. 508\u2013516 (2017)"},{"key":"41_CR4","doi-asserted-by":"crossref","unstructured":"Buchbinder, N., Feldman, M., Schwartz, R.: Online submodular maximization with preemption. In: Proceedings of the 26th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1202\u20131216 (2015)","DOI":"10.1137\/1.9781611973730.80"},{"key":"41_CR5","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.tcs.2021.01.020","volume":"858","author":"Z Liu","year":"2021","unstructured":"Liu, Z., Chen, L., Chang, H., Du, D., Zhang, X.: Online algorithms for BP functions maximization. Theoret. Comput. Sci. 858, 114\u2013121 (2021)","journal-title":"Theoret. Comput. Sci."},{"issue":"3","key":"41_CR6","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/0166-218X(84)90003-9","volume":"7","author":"M Conforti","year":"1984","unstructured":"Conforti, M., Cornu\u00e9jols, G.: Submodular set functions, matroids and the greedy algorithm: tight worst-case bounds and some generalizations of the Rado-Edmonds theorem. Discret. Appl. Math. 7(3), 251\u2013274 (1984)","journal-title":"Discret. Appl. Math."},{"key":"41_CR7","unstructured":"Gomes, R., Krause, A.: Budgeted nonparametric learning from data streams. In: Proceedings of the 27th International Conference on Machine Learning, pp. 391\u2013398 (2010)"},{"key":"41_CR8","unstructured":"Halabi, M. E., Mitrovi, S., Norouzi-Fard, A., Tardos, J., Tarnawski, J.: Fairness in streaming submodular maximization: algorithms and hardness. In: Proceedings of Annual Conference on Neural Information Processing Systems (2020, to appear)"},{"key":"41_CR9","unstructured":"Kazemi, E., Minaee, S., Feldman, M., Karbasi, A.: Regularized submodular maximization at scale. In: Proceedings of the 38th International Conference on Machine Learning, pp. 5356\u20135366 (2021)"},{"key":"41_CR10","unstructured":"Kazemi, E., Mitrovic, M., Zadimoghaddam, M., Lattanzi, S., Karbasi, A.: Submodular streaming in all its glory: tight approximation, minimum memory and low adaptive complexity. In: Proceedings of the 36th International Conference on Machine Learning, pp. 3311\u20133320 (2019)"},{"key":"41_CR11","doi-asserted-by":"crossref","unstructured":"Kempe, D., Kleinberg, J., Tardos, \u00c9.: Maximizing the spread of influence through a social network. In: Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 137\u2013146 (2003)","DOI":"10.1145\/956750.956769"},{"issue":"4","key":"41_CR12","first-page":"2761","volume":"9","author":"A Krause","year":"2008","unstructured":"Krause, A., McMahan, H.B., Guestrin, C., Gupta, A.: Robust submodular observation selection. J. Mach. Learn. Res. 9(4), 2761\u20132801 (2008)","journal-title":"J. Mach. Learn. Res."},{"key":"41_CR13","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1007\/s10898-021-01063-6","volume":"82","author":"Z Liu","year":"2022","unstructured":"Liu, Z., Guo, L., Du, D., Xu, D., Zhang, X.: Maximization problems of balancing submodular relevance and supermodular diversity. J. Glob. Optim. 82, 179\u2013194 (2022). https:\/\/doi.org\/10.1007\/s10898-021-01063-6","journal-title":"J. Glob. Optim."},{"key":"41_CR14","unstructured":"Norouzi-Fard, A., Tarnawski, J., Mitrovi\u0107, S., Zandieh, A., Mousavifar, A., Svensson, O.: Beyond $$1\/2$$-approximation for submodular maximization on massive data streams. In: Proceedings of the 35th International Conference on Machine Learning, pp. 3826\u20133835 (2018)"},{"issue":"3","key":"41_CR15","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1007\/s10898-021-01014-1","volume":"80","author":"Z Zhang","year":"2021","unstructured":"Zhang, Z., Du, D., Jiang, Y., Wu, C.: Maximizing DR-submodular+supermodular functions on the integer lattice subject to a cardinality constraint. J. Global Optim. 80(3), 595\u2013616 (2021). https:\/\/doi.org\/10.1007\/s10898-021-01014-1","journal-title":"J. Global Optim."}],"container-title":["Lecture Notes in Computer Science","Parallel and Distributed Computing, Applications and Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-96772-7_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T21:19:14Z","timestamp":1647379154000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-96772-7_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030967710","9783030967727"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-96772-7_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"16 March 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PDCAT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Parallel and Distributed Computing: Applications and Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guangzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pdcat2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cse.sysu.edu.cn\/pdcat2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-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":"97","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":"24","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":"34","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":"25% - 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":"7","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}