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Intell. Syst. Technol."],"published-print":{"date-parts":[[2019,9,30]]},"abstract":"<jats:p>Unlabeled, multi-view data presents a considerable challenge in many real-world data analysis tasks. These data are worth exploring because they often contain complementary information that improves the quality of the analysis results. Clustering with multi-view data is a particularly challenging problem as revealing the complex data structures between many feature spaces demands discriminative features that are specific to the task and, when too few of these features are present, performance suffers. Extreme learning machines (ELMs) are an emerging form of learning model that have shown an outstanding representation ability and superior performance in a range of different learning tasks. Motivated by the promise of this advancement, we have developed a novel multi-view fusion clustering framework based on an ELM, called MVEC. MVEC learns the embeddings from each view of the data via the ELM network, then constructs a single unified embedding according to the correlations and dependencies between each embedding and automatically weighting the contribution of each. This process exposes the underlying clustering structures embedded within multi-view data with a high degree of accuracy. A simple yet efficient solution is also provided to solve the optimization problem within MVEC. Experiments and comparisons on eight different benchmarks from different domains confirm MVEC\u2019s clustering accuracy.<\/jats:p>","DOI":"10.1145\/3340268","type":"journal-article","created":{"date-parts":[[2019,10,10]],"date-time":"2019-10-10T13:13:05Z","timestamp":1570713185000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Multi-View Fusion with Extreme Learning Machine for Clustering"],"prefix":"10.1145","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5817-1732","authenticated-orcid":false,"given":"Yongshan","family":"Zhang","sequence":"first","affiliation":[{"name":"China University of Geosciences, Wuhan, Hubei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1371-5801","authenticated-orcid":false,"given":"Jia","family":"Wu","sequence":"additional","affiliation":[{"name":"Macquarie University, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9700-247X","authenticated-orcid":false,"given":"Chuan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihua","family":"Cai","sequence":"additional","affiliation":[{"name":"China University of Geosciences, Wuhan, Hubei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Yang","sequence":"additional","affiliation":[{"name":"Macquarie University, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philip S.","family":"Yu","sequence":"additional","affiliation":[{"name":"University of Illinois at Chicago, Chicago, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2004.10095"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.08.024"},{"volume-title":"Proceedings of the 23rd International Joint Conference on Artificial Intelligence. 2598--2604","year":"2013","author":"Cai Xiao","key":"e_1_2_1_3_1"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995740"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2011.09.015"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553391"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.482"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04180-8_45"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.11.015"},{"volume-title":"Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. 356--364","author":"He Lifang","key":"e_1_2_1_10_1"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2012.12.063"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2681670"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2015.06.002"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2307349"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2011.2168604"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2570569"},{"key":"e_1_2_1_17_1","first-page":"31","article-title":"Representational learning with ELMs for big data","volume":"28","author":"Chamara Kasun Liyanaarachchi Lekamalage","year":"2013","journal-title":"IEEE Intelligent Systems"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835449.1835633"},{"key":"e_1_2_1_19_1","unstructured":"Abhishek Kumar Piyush Rai and Hal Daume. 2011. 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