{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:02:14Z","timestamp":1750309334205,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":35,"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"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671794","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:55:12Z","timestamp":1724561712000},"page":"107-118","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Improved Active Covering via Density-Based Space Transformation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1814-1293","authenticated-orcid":false,"given":"MohammadHossein","family":"Bateni","sequence":"first","affiliation":[{"name":"Google Research, New York City, New York, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8130-6631","authenticated-orcid":false,"given":"Hossein","family":"Esfandiari","sequence":"additional","affiliation":[{"name":"Google Research, London, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4147-3181","authenticated-orcid":false,"given":"Samira","family":"HosseinGhorban","sequence":"additional","affiliation":[{"name":"School of Computer Science, Institute for Research in Fundamental Sciences, Tehran, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3262-9332","authenticated-orcid":false,"given":"Alipasha","family":"Montaseri","sequence":"additional","affiliation":[{"name":"Sharif University of Technology, Tehran, Iran"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"volume-title":"Active learning for imbalanced datasets","author":"Aggarwal Umang","key":"e_1_3_2_2_1_1","unstructured":"Umang Aggarwal, Adrian Popescu, and C\u00e9line Hudelot. 2020. Active learning for imbalanced datasets. In IEEE\/CVF-WACV. 1428--1437."},{"volume-title":"Credit card fraud detection using machine learning techniques: A comparative analysis","author":"Awoyemi John O","key":"e_1_3_2_2_2_1","unstructured":"John O Awoyemi, Adebayo O Adetunmbi, and Samuel A Oluwadare. 2017. Credit card fraud detection using machine learning techniques: A comparative analysis. In ICCNI. IEEE, 1--9."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2008.02.021"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"crossref","unstructured":"Avrim Blum. 1990. Learning boolean functions in an infinite attribute space. In STOC. 64--72.","DOI":"10.1145\/100216.100224"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1995.1004"},{"key":"e_1_3_2_2_6_1","volume-title":"NeurIPS","volume":"23","author":"Chaudhuri Kamalika","year":"2010","unstructured":"Kamalika Chaudhuri and Sanjoy Dasgupta. 2010. Rates of convergence for the cluster tree. NeurIPS, Vol. 23 (2010)."},{"key":"e_1_3_2_2_7_1","first-page":"11933","article-title":"Batch active learning at scale","volume":"34","author":"Citovsky Gui","year":"2021","unstructured":"Gui Citovsky, Giulia DeSalvo, Claudio Gentile, Lazaros Karydas, Anand Rajagopalan, Afshin Rostamizadeh, and Sanjiv Kumar. 2021. Batch active learning at scale. NeurIPS, Vol. 34 (2021), 11933--11944.","journal-title":"NeurIPS"},{"key":"e_1_3_2_2_8_1","volume-title":"Improving generalization with active learning. Machine learning","author":"Cohn David","year":"1994","unstructured":"David Cohn, Les Atlas, and Richard Ladner. 1994. Improving generalization with active learning. Machine learning, Vol. 15 (1994), 201--221."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/1622737.1622744"},{"key":"e_1_3_2_2_10_1","volume-title":"A plug-in approach to support estimation. The Annals of Statistics","author":"Cuevas Antonio","year":"1997","unstructured":"Antonio Cuevas and Ricardo Fraiman. 1997. A plug-in approach to support estimation. The Annals of Statistics (1997), 2300--2312."},{"key":"e_1_3_2_2_11_1","first-page":"480","article-title":"Detection of abnormal behavior via nonparametric estimation of the support","volume":"38","author":"Devroye Luc","year":"1980","unstructured":"Luc Devroye and Gary L Wise. 1980. Detection of abnormal behavior via nonparametric estimation of the support. SIDMA, Vol. 38, 3 (1980), 480--488.","journal-title":"SIDMA"},{"key":"e_1_3_2_2_12_1","unstructured":"Yarin Gal Riashat Islam and Zoubin Ghahramani. 2017. Deep bayesian active learning with image data. In ICML. PMLR 1183--1192."},{"key":"e_1_3_2_2_13_1","volume-title":"Bayesian optimal active search and surveying. arXiv preprint arXiv:1206.6406","author":"Garnett Roman","year":"2012","unstructured":"Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong, Jeff Schneider, and Richard Mann. 2012. Bayesian optimal active search and surveying. arXiv preprint arXiv:1206.6406 (2012)."},{"key":"e_1_3_2_2_14_1","volume-title":"ICASSP","volume":"4","author":"Hakkani-T\u00fcr Dilek","year":"2002","unstructured":"Dilek Hakkani-T\u00fcr, Giuseppe Riccardi, and Allen Gorin. 2002. Active learning for automatic speech recognition. In ICASSP, Vol. 4. IEEE, IV--3904."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.5555\/1709418.1709419"},{"key":"e_1_3_2_2_16_1","volume-title":"NeurIPS","volume":"32","author":"Jain Lalit","year":"2019","unstructured":"Lalit Jain and Kevin G Jamieson. 2019. A new perspective on pool-based active classification and false-discovery control. NeurIPS, Vol. 32 (2019)."},{"key":"e_1_3_2_2_17_1","unstructured":"Heinrich Jiang and Afshin Rostamizadeh. 2021. Active Covering. In ICML. PMLR 5013--5022."},{"key":"e_1_3_2_2_18_1","volume-title":"NeurIPS","volume":"32","author":"Jiang Shali","year":"2019","unstructured":"Shali Jiang, Roman Garnett, and Benjamin Moseley. 2019. Cost effective active search. NeurIPS, Vol. 32 (2019)."},{"key":"e_1_3_2_2_19_1","volume-title":"NeurIPS","volume":"31","author":"Jiang Shali","year":"2018","unstructured":"Shali Jiang, Gustavo Malkomes, Matthew Abbott, Benjamin Moseley, and Roman Garnett. 2018. Efficient nonmyopic batch active search. NeurIPS, Vol. 31 (2018)."},{"volume-title":"Multi-class active learning for image classification","author":"Joshi Ajay J","key":"e_1_3_2_2_20_1","unstructured":"Ajay J Joshi, Fatih Porikli, and Nikolaos Papanikolopoulos. 2009. Multi-class active learning for image classification. In CVPR. IEEE, 2372--2379."},{"key":"e_1_3_2_2_21_1","volume-title":"Tackling Provably Hard Representative Selection via Graph Neural Networks. arXiv preprint arXiv:2205.10403","author":"Kazemi Seyed Mehran","year":"2022","unstructured":"Seyed Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, and Vahab Mirrokni. 2022. Tackling Provably Hard Representative Selection via Graph Neural Networks. arXiv preprint arXiv:2205.10403 (2022)."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbankfin.2010.06.001"},{"key":"e_1_3_2_2_23_1","first-page":"3","article-title":"Estimation of the density support and its functionals","volume":"29","author":"Korostelev Alexander P","year":"1993","unstructured":"Alexander P Korostelev and Aleksandr Borisovich Tsybakov. 1993. Estimation of the density support and its functionals. Problemy Peredachi Informatsii, Vol. 29, 1 (1993), 3--18.","journal-title":"Problemy Peredachi Informatsii"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2008.143"},{"volume-title":"On-line learning with an oblivious environment and the power of randomization","author":"Maass Wolfgang","key":"e_1_3_2_2_25_1","unstructured":"Wolfgang Maass. 1991. On-line learning with an oblivious environment and the power of randomization. International Computer Science Institute."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Venkata Vamsikrishna Meduri Lucian Popa Prithviraj Sen and Mohamed Sarwat. 2020. A comprehensive benchmark framework for active learning methods in entity matching. In SIGMOD. 1133--1147.","DOI":"10.1145\/3318464.3380597"},{"volume-title":"Probability and computing: Randomization and probabilistic techniques in algorithms and data analysis","author":"Mitzenmacher Michael","key":"e_1_3_2_2_27_1","unstructured":"Michael Mitzenmacher and Eli Upfal. 2017. Probability and computing: Randomization and probabilistic techniques in algorithms and data analysis. Cambridge university press."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"crossref","unstructured":"Chikashi Nobata Joel Tetreault Achint Thomas Yashar Mehdad and Yi Chang. 2016. Abusive language detection in online user content. In WWW. 145--153.","DOI":"10.1145\/2872427.2883062"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1038\/aps.2012.109"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-020-01562-1"},{"key":"e_1_3_2_2_31_1","volume-title":"A survey of active learning for text classification using deep neural networks. arXiv preprint arXiv:2008.07267","author":"Schr\u00f6der Christopher","year":"2020","unstructured":"Christopher Schr\u00f6der and Andreas Niekler. 2020. A survey of active learning for text classification using deep neural networks. arXiv preprint arXiv:2008.07267 (2020)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1214\/08-AOS661"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"crossref","unstructured":"Petr Slav\u00edk. 1996. A tight analysis of the greedy algorithm for set cover. In STOC. 435--441.","DOI":"10.1145\/237814.237991"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jchemed.0c00541"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2022.3195870"}],"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\/3637528.3671794","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671794","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\/3637528.3671794"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":35,"alternative-id":["10.1145\/3637528.3671794","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671794","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"}}]}}