{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:02:13Z","timestamp":1750309333887,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":14,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/https:\/\/doi.org\/10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["SES-1952882"],"award-info":[{"award-number":["SES-1952882"]}],"id":[{"id":"10.13039\/https:\/\/doi.org\/10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671842","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:55:12Z","timestamp":1724561712000},"page":"466-477","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Iterative Weak Learnability and Multiclass AdaBoost"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7917-9151","authenticated-orcid":false,"given":"In-Koo","family":"Cho","sequence":"first","affiliation":[{"name":"Emory University &amp; Hanyang University, Atlanta, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0419-5696","authenticated-orcid":false,"given":"Jonathan A.","family":"Libgober","sequence":"additional","affiliation":[{"name":"University of Southern California, Los Angeles, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3191-1459","authenticated-orcid":false,"given":"Cheng","family":"Ding","sequence":"additional","affiliation":[{"name":"Emory University, ATLANTA, GA, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1995.1008"},{"key":"e_1_3_2_2_2_1","volume-title":"Machine learning for strategic inference. arXiv preprint arXiv:2101.09613","author":"Cho In-Koo","year":"2021","unstructured":"In-Koo Cho and Jonathan Libgober. 2021. Machine learning for strategic inference. arXiv preprint arXiv:2101.09613 (2021)."},{"key":"e_1_3_2_2_3_1","article-title":"Multiclass Learnability and the ERM Principle","volume":"16","author":"Daniely Amit","year":"2015","unstructured":"Amit Daniely, Sivan Sabato, Shai Ben-David, and Shai Shalev-Shwartz. 2015. Multiclass Learnability and the ERM Principle. Journal of Machine Learning Research, Vol. 16 (December 2015), 2377--2404.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1997.1504"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1016218223"},{"key":"e_1_3_2_2_6_1","volume-title":"Greedy function approximation: a gradient boosting machine. Annals of statistics","author":"Friedman Jerome H","year":"2001","unstructured":"Jerome H Friedman. 2001. Greedy function approximation: a gradient boosting machine. Annals of statistics (2001), 1189--1232."},{"key":"e_1_3_2_2_7_1","article-title":"VC Theory of Large Margin Multi-Category Classifiers","volume":"8","author":"Guermeur Yann","year":"2007","unstructured":"Yann Guermeur. 2007. VC Theory of Large Margin Multi-Category Classifiers. Journal of Machine Learning Research, Vol. 8 (November 2007), 2551--2594.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_8_1","volume-title":"University of California at Irvine (UCI) repository of machine learning databases. Available ftp:\/ftp. ics. uci. edu\/pub\/machine-learning-databases","author":"Mertz J","year":"2005","unstructured":"J Mertz and PM Murphy. 2005. University of California at Irvine (UCI) repository of machine learning databases. Available ftp:\/ftp. ics. uci. edu\/pub\/machine-learning-databases (2005)."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/2567709.2502596"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1022605311895"},{"key":"e_1_3_2_2_11_1","volume-title":"Scikit-learn: Machine learning in Python. the Journal of machine Learning research","author":"Pedregosa Fabian","year":"2011","unstructured":"Fabian Pedregosa, Ga\u00ebl Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al. 2011. Scikit-learn: Machine learning in Python. the Journal of machine Learning research, Vol. 12 (2011), 2825--2830."},{"key":"e_1_3_2_2_12_1","volume-title":"Schapire and Yoav Freund","author":"Robert","year":"2012","unstructured":"Robert E. Schapire and Yoav Freund. 2012. Boosting: Foundations and Algorithms. MIT Press."},{"key":"e_1_3_2_2_13_1","first-page":"5","article-title":"Boosting the margin: A new explanation for the effectiveness of voting methods","volume":"26","author":"Schapire Robert E.","year":"1998","unstructured":"Robert E. Schapire, Yoav Freund, Peter Bartlett, and Wee Sun Lee. 1998. Boosting the margin: A new explanation for the effectiveness of voting methods. Annals of Statistics, Vol. 26, 5 (October 1998), 1651--1686.","journal-title":"Annals of Statistics"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.4310\/SII.2009.v2.n3.a8"}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Barcelona Spain","acronym":"KDD '24"},"container-title":["Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671842","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671842","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:04:14Z","timestamp":1750291454000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671842"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":14,"alternative-id":["10.1145\/3637528.3671842","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671842","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}