{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T13:13:47Z","timestamp":1775913227184,"version":"3.50.1"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council through the Discovery Project","doi-asserted-by":"publisher","award":["DP190101733"],"award-info":[{"award-number":["DP190101733"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1109\/tcyb.2021.3109796","type":"journal-article","created":{"date-parts":[[2021,10,7]],"date-time":"2021-10-07T02:53:27Z","timestamp":1633575207000},"page":"2110-2123","source":"Crossref","is-referenced-by-count":17,"title":["Evolving Gradient Boost: A Pruning Scheme Based on Loss Improvement Ratio for Learning Under Concept Drift"],"prefix":"10.1109","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2711-6233","authenticated-orcid":false,"given":"Kun","family":"Wang","sequence":"first","affiliation":[{"name":"Australia Artificial Intelligence Institute, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0690-4732","authenticated-orcid":false,"given":"Jie","family":"Lu","sequence":"additional","affiliation":[{"name":"Australia Artificial Intelligence Institute, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0733-7138","authenticated-orcid":false,"given":"Anjin","family":"Liu","sequence":"additional","affiliation":[{"name":"Australia Artificial Intelligence Institute, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3960-0583","authenticated-orcid":false,"given":"Guangquan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Australia Artificial Intelligence Institute, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Management, Shanghai University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2876857"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2983962"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3051406"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/2523813"},{"key":"ref5","first-page":"211","article-title":"Pruning adaptive boosting","volume-title":"Proc. 14th Int. Conf. Mach. Learn.","volume":"97","author":"Margineantu"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1201\/b12207"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143921"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-59119-2_166"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.2307\/2699986"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.02.004"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2004.10091"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(02)00190-X"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.06.030"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.07.037"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/502512.502568"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-019-05840-z"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557041"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ISCMI.2017.8279591"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15880-3_15"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2019.00158"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2018.2796099"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611975673.75"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357946"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2019.00021"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3205453"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33012446"},{"key":"ref27","volume-title":"Wavelet decomposition of gradient boosting","author":"Dekel","year":"2018"},{"key":"ref28","first-page":"1551","article-title":"Cost efficient gradient boosting","volume-title":"Proc. 31st Int. Conf. Neural Inf. Process. Syst.","author":"Peter"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080725"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2014.01.001"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623609"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2341031"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2871120"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2015.09.009"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-017-5642-8"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148216"},{"key":"ref37","first-page":"2755","article-title":"Dynamic weighted majority: An ensemble method for drifting concepts","volume":"8","author":"Kolter","year":"2007","journal-title":"J. Mach. Learn. Res."},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-21222-2_19"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.136"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2013.2251352"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2016.2599855"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.11.004"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2009.5457447"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICSMC.2005.1571498"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2609424"},{"key":"ref46","first-page":"489","article-title":"DART: Dropouts meet multiple additive regression trees","volume-title":"Proc. Artif. Intell. Stat.","author":"Vinayak"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.119"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207077"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1177\/001316446002000104"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1023\/A:I0I0933404324"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2011.2160459"},{"key":"ref52","first-page":"3146","article-title":"LightGBM: A highly efficient gradient boosting decision tree","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Ke"},{"key":"ref53","first-page":"1601","article-title":"MOA: Massive online analysis","volume":"11","author":"Bifet","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"ref54","first-page":"142","article-title":"Learning word vectors for sentiment analysis","volume-title":"Proc. 49th Annu. Meeting Assoc. Comput. Linguist. Human Lang. Technol.","author":"Maas"},{"key":"ref55","volume-title":"MNIST Handwritten Digit Database","author":"LeCun","year":"2010"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2775225"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/10073969\/09562149.pdf?arnumber=9562149","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T23:38:45Z","timestamp":1705016325000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9562149\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4]]},"references-count":56,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2021.3109796","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4]]}}}