{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:43:12Z","timestamp":1762868592620,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,7,11]],"date-time":"2021-07-11T00:00:00Z","timestamp":1625961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["IIS-1838615,IIS-1618948,IIS-1553568"],"award-info":[{"award-number":["IIS-1838615,IIS-1618948,IIS-1553568"]}],"id":[{"id":"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":[[2021,7,11]]},"DOI":"10.1145\/3404835.3462852","type":"proceedings-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T02:41:54Z","timestamp":1626057714000},"page":"1410-1419","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution"],"prefix":"10.1145","author":[{"given":"Chuanhao","family":"Li","sequence":"first","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyun","family":"Wu","sequence":"additional","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongning","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,7,11]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Yasin Abbasi-yadkori D\u00e1vid P\u00e1l and Csaba Szepesv\u00e1ri. 2011. Improved Algorithms for Linear Stochastic Bandits. In NIPS. 2312--2320."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1214\/17-EJS1341SI"},{"key":"e_1_3_2_2_3_1","volume-title":"Bayesian online changepoint detection. arXiv preprint arXiv:0710.3742","author":"Adams Ryan Prescott","year":"2007","unstructured":"Ryan Prescott Adams and David JC MacKay. 2007. Bayesian online changepoint detection. arXiv preprint arXiv:0710.3742 (2007)."},{"key":"e_1_3_2_2_4_1","volume-title":"Proceedings of the 30th ICML. 1220--1228","author":"Agrawal Shipra","year":"2013","unstructured":"Shipra Agrawal and Navin Goyal. 2013. Thompson Sampling for Contextual Bandits with Linear Payoffs. In Proceedings of the 30th ICML. 1220--1228."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176342871"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1013689704352"},{"key":"e_1_3_2_2_7_1","volume-title":"Conference on Learning Theory. 138--158","author":"Auer Peter","year":"2019","unstructured":"Peter Auer, Pratik Gajane, and Ronald Ortner. 2019. Adaptively tracking the best bandit arm with an unknown number of distribution changes. In Conference on Learning Theory. 138--158."},{"key":"e_1_3_2_2_9_1","unstructured":"Nicolo Cesa-Bianchi Claudio Gentile and Giovanni Zappella. 2013. A gang of bandits. (2013) 737--745."},{"key":"e_1_3_2_2_10_1","volume-title":"An Empirical Evaluation of Thompson Sampling. In NIPS","author":"Chapelle Olivier","year":"2011","unstructured":"Olivier Chapelle and Lihong Li. 2011. An Empirical Evaluation of Thompson Sampling. In NIPS 2011. 2249--2257."},{"key":"e_1_3_2_2_11_1","volume-title":"A new algorithm for non-stationary contextual bandits: Efficient, optimal, and parameter-free. arXiv preprint arXiv:1902.00980","author":"Chen Yifang","year":"2019","unstructured":"Yifang Chen, Chung-Wei Lee, Haipeng Luo, and Chen-Yu Wei. 2019. A new algorithm for non-stationary contextual bandits: Efficient, optimal, and parameter-free. arXiv preprint arXiv:1902.00980 (2019)."},{"volume-title":"The 22nd AISTATS. 1079--1087.","author":"Cheung Wang Chi","key":"e_1_3_2_2_12_1","unstructured":"Wang Chi Cheung, David Simchi-Levi, and Ruihao Zhu. 2019. Learning to optimize under non-stationarity. In The 22nd AISTATS. 1079--1087."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1995.10476550"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176342360"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1177\/001872675400700202"},{"key":"e_1_3_2_2_16_1","unstructured":"Aurlien Garivier and Eric Moulines. [n.d.]. On Upper-Confidence Bound Policies for Non-stationary Bandit Problems. In arXiv preprint arXiv:0805.3415 (2008) ."},{"key":"e_1_3_2_2_17_1","unstructured":"Claudio Gentile Shuai Li Purushottam Kar Alexandros Karatzoglou Giovanni Zappella and Evans Etrue. 2017. On context-dependent clustering of bandits. In ICML. 1253--1262."},{"key":"e_1_3_2_2_18_1","volume-title":"Online Clustering of Bandits. In ICML'14","author":"Gentile Claudio","year":"2014","unstructured":"Claudio Gentile, Shuai Li, and Giovanni Zappella. 2014. Online Clustering of Bandits. In ICML'14. 757--765."},{"volume-title":"24th IJCAI .","author":"Hariri Negar","key":"e_1_3_2_2_19_1","unstructured":"Negar Hariri, Bamshad Mobasher, and Robin Burke. 2015. Adapting to user preference changes in interactive recommendation. In 24th IJCAI ."},{"key":"e_1_3_2_2_20_1","volume-title":"The movielens datasets: History and context. Acm transactions on interactive intelligent systems (tiis)","author":"Maxwell Harper F","year":"2015","unstructured":"F Maxwell Harper and Joseph A Konstan. 2015. The movielens datasets: History and context. Acm transactions on interactive intelligent systems (tiis), Vol. 5, 4 (2015), 1--19."},{"key":"e_1_3_2_2_21_1","unstructured":"Cedric Hartland Sylvain Gelly Nicolas Baskiotis Olivier Teytaud and Michele Sebag. 2006. Multi-armed Bandit Dynamic Environments and Meta-Bandits. (2006)."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.2307\/3212693"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290958"},{"key":"e_1_3_2_2_24_1","unstructured":"Jaya Kawale Hung H Bui Branislav Kveton Long Tran-Thanh and Sanjay Chawla. 2015. Efficient Thompson Sampling for Online Matrix-Factorization Recommendation. In NIPS. 1297--1305."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"volume-title":"Bandit algorithms","author":"Lattimore Tor","key":"e_1_3_2_2_26_1","unstructured":"Tor Lattimore and Csaba Szepesv\u00e1ri. 2020. Bandit algorithms .Cambridge University Press."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772758"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1935826.1935878"},{"key":"e_1_3_2_2_29_1","volume-title":"Improved algorithm on online clustering of bandits. arXiv preprint arXiv:1902.09162","author":"Li Shuai","year":"2019","unstructured":"Shuai Li, Wei Chen, and Kwong-Sak Leung. 2019. Improved algorithm on online clustering of bandits. arXiv preprint arXiv:1902.09162 (2019)."},{"key":"e_1_3_2_2_30_1","volume-title":"Graph clustering bandits for recommendation. arXiv preprint arXiv:1605.00596","author":"Li Shuai","year":"2016","unstructured":"Shuai Li, Claudio Gentile, and Alexandros Karatzoglou. 2016a. Graph clustering bandits for recommendation. arXiv preprint arXiv:1605.00596 (2016)."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911548"},{"key":"e_1_3_2_2_32_1","volume-title":"Conference On Learning Theory. 1739--1776","author":"Luo Haipeng","year":"2018","unstructured":"Haipeng Luo, Chen-Yu Wei, Alekh Agarwal, and John Langford. 2018. Efficient contextual bandits in non-stationary worlds. In Conference On Learning Theory. 1739--1776."},{"key":"e_1_3_2_2_33_1","volume-title":"Thompson sampling in switching environments with bayesian online change point detection. arXiv preprint arXiv:1302.3721","author":"Mellor Joseph","year":"2013","unstructured":"Joseph Mellor and Jonathan Shapiro. 2013. Thompson sampling in switching environments with bayesian online change point detection. arXiv preprint arXiv:1302.3721 (2013)."},{"key":"e_1_3_2_2_34_1","unstructured":"Joshua L Moore Shuo Chen Douglas Turnbull and Thorsten Joachims. 2013. Taste Over Time: The Temporal Dynamics of User Preferences.. In ISMIR. 401--406."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2187836.2187918"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/245108.245121"},{"key":"e_1_3_2_2_37_1","unstructured":"Yoan Russac Claire Vernade and Olivier Capp\u00e9. 2019. Weighted Linear Bandits for Non-Stationary Environments. In NIPS. 12017--12026."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1287\/moor.2014.0650"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/371920.372071"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/1281192.1281269"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Huazheng Wang Qingyun Wu and Hongning Wang. 2017. Factorization Bandits for Interactive Recommendation. In AAAI. 2695--2702.","DOI":"10.1609\/aaai.v31i1.10936"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210051"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911528"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3133025"},{"key":"e_1_3_2_2_45_1","unstructured":"Kaige Yang Laura Toni and Xiaowen Dong. 2020. Laplacian-regularized graph bandits: Algorithms and theoretical analysis. In AISTATS. 3133--3143."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553524"},{"key":"e_1_3_2_2_47_1","volume-title":"Proceedings of the 23rd AISTATS","volume":"2020","author":"Zhao Peng","year":"2020","unstructured":"Peng Zhao, Lijun Zhang, Yuan Jiang, and Zhi-Hua Zhou. 2020. A simple approach for non-stationary linear bandits. In Proceedings of the 23rd AISTATS, Vol. 2020."}],"event":{"name":"SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Virtual Event Canada","acronym":"SIGIR '21"},"container-title":["Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404835.3462852","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3404835.3462852","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3404835.3462852","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:17Z","timestamp":1750193237000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404835.3462852"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,11]]},"references-count":46,"alternative-id":["10.1145\/3404835.3462852","10.1145\/3404835"],"URL":"https:\/\/doi.org\/10.1145\/3404835.3462852","relation":{},"subject":[],"published":{"date-parts":[[2021,7,11]]},"assertion":[{"value":"2021-07-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}