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Knowl. Discov. Data"],"published-print":{"date-parts":[[2023,11,30]]},"abstract":"<jats:p>In multi-label learning, each instance is associated with multiple labels simultaneously. Multi-label data often have noisy, irrelevant, and redundant features of high dimensionality. Multi-label feature selection has received considerable attention as an effective means for dealing with high-dimensional multi-label data. Many multi-label feature selection methods exploit label correlations to help select features. However, finding label correlations and selecting features in existing multi-label feature selection methods are often two separate processes, the existence of noises and outliers in training data makes the label correlations exploited from label space less reliable. Therefore, the learned label correlations may mislead the feature selection process and result in the selection of less informative features. This article proposes a novel algorithm named ROAD, i.e., multi-label featuRe selectiOn via ADaptive label correlation estimation. ROAD jointly performs adaptive label correlation exploration and feature selection with alternating optimization to obtain reliable estimation of label correlations, which can more effectively reveal the intrinsic manifold structure among labels and lead to the selection of a more proper feature subset. Comprehensive experiments on several frequently used datasets validate the superiority of ROAD against the state-of-the-art multi-label feature selection algorithms.<\/jats:p>","DOI":"10.1145\/3604560","type":"journal-article","created":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T11:28:16Z","timestamp":1686396496000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":32,"title":["Multi-Label Feature Selection Via Adaptive Label Correlation Estimation"],"prefix":"10.1145","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6383-1683","authenticated-orcid":false,"given":"Zan","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China), Hefei University of Technology; School of Computer Science and Information Engineering, Hefei University of Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-6768-6071","authenticated-orcid":false,"given":"Zhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Engineering, HefeiUniversity of Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3787-4583","authenticated-orcid":false,"given":"Jialu","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Engineering, HefeiUniversity of Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2843-5738","authenticated-orcid":false,"given":"Lin","family":"Liu","sequence":"additional","affiliation":[{"name":"UniSA STEM, University of South Australia, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9023-1878","authenticated-orcid":false,"given":"Jiuyong","family":"Li","sequence":"additional","affiliation":[{"name":"UniSA STEM, University of South Australia, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2289-1679","authenticated-orcid":false,"given":"Gongqing","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China), Hefei University of Technology; School of Computer Science and Information Engineering, Hefei University of Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2396-1704","authenticated-orcid":false,"given":"Xindong","family":"Wu","sequence":"additional","affiliation":[{"name":"Knowledge Engineering Research Center, Zhejiang Lab, China; Key Laboratory ofKnowledge Engineering with Big Data (the Ministry of Education of China), Hefei University of Technology, China"}]}],"member":"320","published-online":{"date-parts":[[2023,8,10]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/361573.361582"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-022-01616-5"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-017-0647-y"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.10.022"},{"key":"e_1_3_2_7_2","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"Dem\u0161ar Janez","year":"2006","unstructured":"Janez Dem\u0161ar. 2006. 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