{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T07:01:47Z","timestamp":1760598107571,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":14,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Agency for Science, Technology and Research","award":["Grant No. A1898b0043"],"award-info":[{"award-number":["Grant No. A1898b0043"]}]},{"DOI":"10.13039\/501100001773","name":"University of New South Wales","doi-asserted-by":"publisher","award":["UIPA"],"award-info":[{"award-number":["UIPA"]}],"id":[{"id":"10.13039\/501100001773","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,26]]},"DOI":"10.1145\/3459637.3482091","type":"proceedings-article","created":{"date-parts":[[2021,11,15]],"date-time":"2021-11-15T15:31:19Z","timestamp":1636990279000},"page":"2970-2973","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Does Adversarial Oversampling Help us?"],"prefix":"10.1145","author":[{"given":"Tanmoy","family":"Dam","sequence":"first","affiliation":[{"name":"University of New South Wales, Canberra, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Md Meftahul","family":"Ferdaus","sequence":"additional","affiliation":[{"name":"Agency for Science, Technology and Research (A*STAR), Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sreenatha G.","family":"Anavatti","sequence":"additional","affiliation":[{"name":"University of New South Wales, Canberra, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Senthilnath","family":"Jayavelu","sequence":"additional","affiliation":[{"name":"Agency for Science, Technology and Research (A*STAR), Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hussein A","family":"Abbass","sequence":"additional","affiliation":[{"name":"University of New South Wales, Canberra, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/1622407.1622416"},{"key":"e_1_3_2_1_2_1","volume-title":"Complement objective training. arXiv preprint arXiv:1903.01182","author":"Chen Hao-Yun","year":"2019","unstructured":"Hao-Yun Chen , Pei-Hsin Wang , Chun-Hao Liu , Shih-Chieh Chang , Jia-Yu Pan , Yu-Ting Chen , Wei Wei , and Da-Cheng Juan . 2019. Complement objective training. arXiv preprint arXiv:1903.01182 ( 2019 ). Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, and Da-Cheng Juan. 2019. Complement objective training. arXiv preprint arXiv:1903.01182 (2019)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.09.030"},{"key":"e_1_3_2_1_4_1","volume-title":"Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels. arXiv preprint arXiv:2105.04522","author":"Englesson Erik","year":"2021","unstructured":"Erik Englesson and Hossein Azizpour . 2021. Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels. arXiv preprint arXiv:2105.04522 ( 2021 ). Erik Englesson and Hossein Azizpour. 2021. Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels. arXiv preprint arXiv:2105.04522 (2021)."},{"key":"e_1_3_2_1_5_1","volume-title":"Generative adversarial networks. arXiv preprint arXiv:1406.2661","author":"Goodfellow Ian J","year":"2014","unstructured":"Ian J Goodfellow , Jean Pouget-Abadie , Mehdi Mirza , Bing Xu , David Warde-Farley , Sherjil Ozair , Aaron Courville , and Yoshua Bengio . 2014. Generative adversarial networks. arXiv preprint arXiv:1406.2661 ( 2014 ). Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative adversarial networks. arXiv preprint arXiv:1406.2661 (2014)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295327"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/11538059_91"},{"key":"e_1_3_2_1_8_1","volume-title":"ADASYN: Adaptive synthetic sampling approach for imbalanced learning. In 2008 IEEE international joint conference on neural networks","author":"He Haibo","year":"2008","unstructured":"Haibo He , Yang Bai , Edwardo A Garcia , and Shutao Li . 2008 . ADASYN: Adaptive synthetic sampling approach for imbalanced learning. In 2008 IEEE international joint conference on neural networks (IEEE world congress on computational intelligence). IEEE , 1322--1328. Haibo He, Yang Bai, Edwardo A Garcia, and Shutao Li. 2008. ADASYN: Adaptive synthetic sampling approach for imbalanced learning. In 2008 IEEE international joint conference on neural networks (IEEE world congress on computational intelligence). IEEE, 1322--1328."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2008.239"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.580"},{"key":"e_1_3_2_1_11_1","volume-title":"Proc. of the Int'l Conf. on Artificial Intelligence","volume":"56","author":"Japkowicz Nathalie","year":"2000","unstructured":"Nathalie Japkowicz . 2000 . The class imbalance problem: Significance and strategies . In Proc. of the Int'l Conf. on Artificial Intelligence , Vol. 56 . Citeseer. Nathalie Japkowicz. 2000. The class imbalance problem: Significance and strategies. In Proc. of the Int'l Conf. on Artificial Intelligence, Vol. 56. Citeseer."},{"key":"e_1_3_2_1_12_1","unstructured":"Moshe Lichman et al. 2013. UCI machine learning repository.  Moshe Lichman et al. 2013. UCI machine learning repository."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00178"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295446"}],"event":{"name":"CIKM '21: The 30th ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Virtual Event Queensland Australia","acronym":"CIKM '21"},"container-title":["Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482091","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3459637.3482091","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:12Z","timestamp":1750188612000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482091"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":14,"alternative-id":["10.1145\/3459637.3482091","10.1145\/3459637"],"URL":"https:\/\/doi.org\/10.1145\/3459637.3482091","relation":{},"subject":[],"published":{"date-parts":[[2021,10,26]]},"assertion":[{"value":"2021-10-30","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}