{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T04:47:26Z","timestamp":1742964446457,"version":"3.40.3"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030041816"},{"type":"electronic","value":"9783030041823"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-04182-3_58","type":"book-chapter","created":{"date-parts":[[2018,11,17]],"date-time":"2018-11-17T10:19:48Z","timestamp":1542449988000},"page":"660-672","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Heterogeneous Dyadic Multi-task Learning with Implicit Feedback"],"prefix":"10.1007","author":[{"given":"Simon","family":"Moura","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amir","family":"Asarbaev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Massih-Reza","family":"Amini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yury","family":"Maximov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,18]]},"reference":[{"key":"58_CR1","doi-asserted-by":"crossref","unstructured":"Bennett, J., Lanning, S.: The Netflix prize. In: KDD Cup and Workshop 2007, p.\u00a035 (2007)","DOI":"10.1145\/1345448.1345459"},{"key":"58_CR2","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1007\/978-3-540-45167-9_41","volume-title":"Learning Theory and Kernel Machines","author":"S Ben-David","year":"2003","unstructured":"Ben-David, S., Schuller, R.: Exploiting task relatedness for multiple task learning. In: Sch\u00f6lkopf, B., Warmuth, M.K. (eds.) COLT-Kernel 2003. LNCS (LNAI), vol. 2777, pp. 567\u2013580. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/978-3-540-45167-9_41"},{"issue":"1","key":"58_CR3","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1023\/A:1007379606734","volume":"28","author":"R Caruana","year":"1997","unstructured":"Caruana, R.: Multitask Learning. Mach. Learn. 28(1), 41\u201375 (1997)","journal-title":"Mach. Learn."},{"key":"58_CR4","unstructured":"Yang, X., Seyoung, K., Xing, E.P.: Heterogeneous multi-task learning with joint sparsity constraints. In: Advances in Neural Information Processing Systems 22, Vancouver, pp. 2151\u20132159 (2009)"},{"key":"58_CR5","doi-asserted-by":"crossref","unstructured":"Sculley, D.: Combined regression and ranking. In: 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, pp. 979\u2013988 (2010)","DOI":"10.1145\/1835804.1835928"},{"key":"58_CR6","unstructured":"Kumar, A., Daume, H.: Learning task grouping and overlap in multi-task learning. In: 29th International Conference on Machine Learning, New York, pp. 1383\u20131390 (2012)"},{"key":"58_CR7","doi-asserted-by":"crossref","unstructured":"Chapelle, O., Shivaswamy, P., Vadrevu, S., Weinberger, K., Zhang, Y., Tseng, B.: Multi-task learning for boosting with application to web search ranking. In: 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, pp. 1189\u20131198 (2010)","DOI":"10.1145\/1835804.1835953"},{"key":"58_CR8","doi-asserted-by":"crossref","unstructured":"Evgeniou, T., Pontil, M.: Regularized multi-task learning. In: 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, pp. 109\u2013117 (2004)","DOI":"10.1145\/1014052.1014067"},{"key":"58_CR9","unstructured":"Stock, M., Pahikkala, T., Airola, A., De Baets, B., Waegeman, W.: Efficient Pairwise Learning using Kernel Ridge Regression: an Exact Two-Step Method. Technical report (2016)"},{"key":"58_CR10","unstructured":"Volkovs, M., Zemel, R.S.: Collaborative ranking with 17 parameters. In: Advances in Neural Information Processing Systems 25, Lake Tahoe, pp. 2294\u20132302 (2012)"},{"key":"58_CR11","series-title":"Springer Texts in Statistics","doi-asserted-by":"publisher","DOI":"10.1007\/0-387-27605-X","volume-title":"Testing Statistical Hypotheses","author":"EL Lehmann","year":"2005","unstructured":"Lehmann, E.L., Romano, J.P.: Testing Statistical Hypotheses. Springer Texts in Statistics. Springer, New York (2005). https:\/\/doi.org\/10.1007\/0-387-27605-X"}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-04182-3_58","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T15:25:10Z","timestamp":1709825110000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-04182-3_58"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030041816","9783030041823"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-04182-3_58","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"18 November 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Siem Reap","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambodia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 December 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conference.cs.cityu.edu.hk\/iconip\/","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":"575","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":"401","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":"70% - 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":"4","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)"}}]}}