{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T17:13:51Z","timestamp":1778346831264,"version":"3.51.4"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030161415","type":"print"},{"value":"9783030161422","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-16142-2_10","type":"book-chapter","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T02:50:37Z","timestamp":1554346237000},"page":"119-130","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Auto-encoder Based Co-training Multi-view Representation Learning"],"prefix":"10.1007","author":[{"given":"Run-kun","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian-wei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan-fang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao-jie","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,3,20]]},"reference":[{"key":"10_CR1","unstructured":"Bickel, S., Scheffer, T.: Multi-view clustering. In: Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), Brighton, UK, 1\u20134 November 2004, pp. 19\u201326 (2004)"},{"key":"10_CR2","doi-asserted-by":"crossref","unstructured":"Blum, A., Mitchell, T.M.: Combining labeled and unlabeled data with co-training. In: Proceedings of the Eleventh Annual Conference on Computational Learning Theory, COLT 1998, Madison, Wisconsin, USA, 24\u201326 July 1998, pp. 92\u2013100 (1998)","DOI":"10.1145\/279943.279962"},{"key":"10_CR3","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1007\/11564096_11","volume-title":"Machine Learning: ECML 2005","author":"U Brefeld","year":"2005","unstructured":"Brefeld, U., B\u00fcscher, C., Scheffer, T.: Multi-view discriminative sequential learning. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.) ECML 2005. LNCS (LNAI), vol. 3720, pp. 60\u201371. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11564096_11"},{"key":"10_CR4","doi-asserted-by":"crossref","unstructured":"Brefeld, U., Scheffer, T.: Co-EM support vector learning. In: Proceedings of the Twenty-First International Conference on Machine Learning, (ICML 2004), Banff, Alberta, Canada, 4\u20138 July 2004 (2004)","DOI":"10.1145\/1015330.1015350"},{"key":"10_CR5","doi-asserted-by":"crossref","unstructured":"Chaudhuri, K., Kakade, S.M., Livescu, K., Sridharan, K.: Multi-view clustering via canonical correlation analysis. In: Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, Montreal, Quebec, Canada, 14\u201318 June 2009, pp. 129\u2013136 (2009)","DOI":"10.1145\/1553374.1553391"},{"key":"10_CR6","unstructured":"Chen, M., Weinberger, K.Q., Chen, Y.: Automatic feature decomposition for single view co-training. In: Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, 28 June\u20132 July 2011, pp. 953\u2013960 (2011)"},{"key":"10_CR7","unstructured":"Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2010, Chia Laguna Resort, Sardinia, Italy, 13\u201315 May 2010, pp. 249\u2013256 (2010)"},{"key":"10_CR8","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1007\/978-3-642-40991-2_23","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"X Jin","year":"2013","unstructured":"Jin, X., Zhuang, F., Wang, S., He, Q., Shi, Z.: Shared structure learning for multiple tasks with multiple views. In: Blockeel, H., Kersting, K., Nijssen, S., \u017delezn\u00fd, F. (eds.) ECML PKDD 2013. LNCS (LNAI), vol. 8189, pp. 353\u2013368. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-40991-2_23"},{"key":"10_CR9","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. CoRR abs\/1312.6114 (2013)"},{"key":"10_CR10","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1007\/978-3-642-13208-7_54","volume-title":"Artificial Intelligence and Soft Computing","author":"O Kursun","year":"2010","unstructured":"Kursun, O., Alpaydin, E.: Canonical correlation analysis for multiview semisupervised feature extraction. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010. LNCS (LNAI), vol. 6113, pp. 430\u2013436. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-13208-7_54"},{"issue":"6","key":"10_CR11","doi-asserted-by":"publisher","first-page":"1233","DOI":"10.1109\/TNNLS.2015.2402203","volume":"26","author":"J Liu","year":"2015","unstructured":"Liu, J., Jiang, Y., Li, Z., Zhou, Z., Lu, H.: Partially shared latent factor learning with multiview data. IEEE Trans. Neural Netw. Learn. Syst. 26(6), 1233\u20131246 (2015)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"10","key":"10_CR12","doi-asserted-by":"publisher","first-page":"12955","DOI":"10.1007\/s11042-017-4926-0","volume":"77","author":"W Ou","year":"2018","unstructured":"Ou, W., Long, F., Tan, Y., Yu, S., Wang, P.: Co-regularized multiview nonnegative matrix factorization with correlation constraint for representation learning. Multimed. Tools Appl. 77(10), 12955\u201312978 (2018)","journal-title":"Multimed. Tools Appl."},{"issue":"10\u201311","key":"10_CR13","doi-asserted-by":"publisher","first-page":"2395","DOI":"10.1016\/j.patcog.2011.04.002","volume":"44","author":"Z Wang","year":"2011","unstructured":"Wang, Z., Chen, S., Gao, D.: A novel multi-view learning developed from single-view patterns. Pattern Recogn. 44(10\u201311), 2395\u20132413 (2011)","journal-title":"Pattern Recogn."},{"key":"10_CR14","unstructured":"Xu, C., Tao, D., Xu, C.: A survey on multi-view learning. CoRR abs\/1304.5634 (2013)"},{"key":"10_CR15","unstructured":"Zeiler, M.D.: ADADELTA: an adaptive learning rate method. CoRR abs\/1212.5701 (2012)"},{"key":"10_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1007\/978-3-319-91458-9_33","volume-title":"Database Systems for Advanced Applications","author":"Z Zhang","year":"2018","unstructured":"Zhang, Z., Qin, Z., Li, P., Yang, Q., Shao, J.: Multi-view discriminative learning via joint non-negative matrix factorization. In: Pei, J., Manolopoulos, Y., Sadiq, S., Li, J. (eds.) DASFAA 2018. LNCS, vol. 10828, pp. 542\u2013557. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-91458-9_33"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-16142-2_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T12:18:34Z","timestamp":1709813914000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-16142-2_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030161415","9783030161422"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-16142-2_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"20 March 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Macau","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.pakdd2019.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":"Microsoft Conf. Man. Toolkit CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"542","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":"137","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":"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":"3.79","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":"5.85","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":"In addition, there were 31 PAKDD 2019 Workshops' papers accepted for publication","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)"}}]}}