{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:45:46Z","timestamp":1765547146546,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":41,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T00:00:00Z","timestamp":1691107200000},"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":[[2023,8,6]]},"DOI":"10.1145\/3580305.3599475","type":"proceedings-article","created":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T18:10:58Z","timestamp":1691172658000},"page":"154-166","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8269-3602","authenticated-orcid":false,"given":"Zeyu","family":"Cao","sequence":"first","affiliation":[{"name":"University of Cambridge, Cambridge, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3101-5673","authenticated-orcid":false,"given":"Zhipeng","family":"Liang","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9598-7642","authenticated-orcid":false,"given":"Bingzhe","family":"Wu","sequence":"additional","affiliation":[{"name":"Tencent AI Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2223-5706","authenticated-orcid":false,"given":"Shu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tencent AI Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9659-3634","authenticated-orcid":false,"given":"Hangyu","family":"Li","sequence":"additional","affiliation":[{"name":"Tencent AI Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2415-652X","authenticated-orcid":false,"given":"Ouyang","family":"Wen","sequence":"additional","affiliation":[{"name":"Tencent AI Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7387-302X","authenticated-orcid":false,"given":"Yu","family":"Rong","sequence":"additional","affiliation":[{"name":"Tencent AI Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8543-3953","authenticated-orcid":false,"given":"Peilin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Tencent AI Lab, Shenzhen, China"}]}],"member":"320","published-online":{"date-parts":[[2023,8,4]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems","author":"Abbasi-Yadkori Yasin","year":"2011","unstructured":"Yasin Abbasi-Yadkori , D\u00e1vid P\u00e1l , and Csaba Szepesv\u00e1ri . 2011. Improved Algorithms for Linear Stochastic Bandits . In Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011 . Proceedings of a meeting held 12-14 December 2011, Granada, Spain, John Shawe-Taylor, Richard S. Zemel, Peter L. Bartlett, Fernando C. N. Pereira, and Kilian Q. Weinberger (Eds .). 2312--2320. https:\/\/proceedings.neurips.cc\/paper\/2011\/hash\/e1d5be1c7f2f456670de3d53c7b54f4a-Abstract.html Yasin Abbasi-Yadkori, D\u00e1vid P\u00e1l, and Csaba Szepesv\u00e1ri. 2011. Improved Algorithms for Linear Stochastic Bandits. In Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, Granada, Spain, John Shawe-Taylor, Richard S. Zemel, Peter L. Bartlett, Fernando C. N. Pereira, and Kilian Q. Weinberger (Eds.). 2312--2320. https:\/\/proceedings.neurips.cc\/paper\/2011\/hash\/e1d5be1c7f2f456670de3d53c7b54f4a-Abstract.html"},{"key":"e_1_3_2_2_2_1","volume-title":"Federated residual learning. arXiv preprint arXiv:2003.12880","author":"Agarwal Alekh","year":"2020","unstructured":"Alekh Agarwal , John Langford , and Chen-Yu Wei . 2020. Federated residual learning. arXiv preprint arXiv:2003.12880 ( 2020 ). Alekh Agarwal, John Langford, and Chen-Yu Wei. 2020. Federated residual learning. arXiv preprint arXiv:2003.12880 (2020)."},{"key":"e_1_3_2_2_3_1","volume-title":"International conference on machine learning. PMLR, 127--135","author":"Agrawal Shipra","year":"2013","unstructured":"Shipra Agrawal and Navin Goyal . 2013 . Thompson sampling for contextual bandits with linear payoffs . In International conference on machine learning. PMLR, 127--135 . Shipra Agrawal and Navin Goyal. 2013. Thompson sampling for contextual bandits with linear payoffs. In International conference on machine learning. PMLR, 127--135."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371832"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539402"},{"key":"e_1_3_2_2_6_1","volume-title":"Vafl: a method of vertical asynchronous federated learning. arXiv preprint arXiv:2007.06081","author":"Chen Tianyi","year":"2020","unstructured":"Tianyi Chen , Xiao Jin , Yuejiao Sun , and Wotao Yin . 2020. Vafl: a method of vertical asynchronous federated learning. arXiv preprint arXiv:2007.06081 ( 2020 ). Tianyi Chen, Xiao Jin, Yuejiao Sun, and Wotao Yin. 2020. Vafl: a method of vertical asynchronous federated learning. arXiv preprint arXiv:2007.06081 (2020)."},{"key":"e_1_3_2_2_7_1","volume-title":"Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data. CoRR","author":"Jiang Juyong","year":"2022","unstructured":"Yiu-ming Cheung, Juyong Jiang , Feng Yu , and Jian Lou . 2022. Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data. CoRR , Vol. abs\/ 2203 .01752 ( 2022 ). https:\/\/doi.org\/10.48550\/arXiv.2203.01752 showeprint[arXiv]2203.01752 10.48550\/arXiv.2203.01752 Yiu-ming Cheung, Juyong Jiang, Feng Yu, and Jian Lou. 2022. Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data. CoRR, Vol. abs\/2203.01752 (2022). https:\/\/doi.org\/10.48550\/arXiv.2203.01752 showeprint[arXiv]2203.01752"},{"key":"e_1_3_2_2_8_1","volume-title":"Differentially-Private Federated Linear Bandits. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020","author":"Dubey Abhimanyu","year":"2020","unstructured":"Abhimanyu Dubey and Alex ' Sandy' Pentland . 2020 . Differentially-Private Federated Linear Bandits. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020 , NeurIPS 2020, December 6-12, 2020, virtual, Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin (Eds.). https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/4311359ed4969e8401880e3c1836fbe1-Abstract.html Abhimanyu Dubey and Alex 'Sandy' Pentland. 2020. Differentially-Private Federated Linear Bandits. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin (Eds.). https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/4311359ed4969e8401880e3c1836fbe1-Abstract.html"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/1791834.1791836"},{"key":"e_1_3_2_2_10_1","volume-title":"Foundations and Trends\u00ae in Theoretical Computer Science","volume":"9","author":"Dwork Cynthia","year":"2014","unstructured":"Cynthia Dwork , Aaron Roth , 2014 . The algorithmic foundations of differential privacy . Foundations and Trends\u00ae in Theoretical Computer Science , Vol. 9 , 3--4 (2014), 211--407. Cynthia Dwork, Aaron Roth, et al. 2014. The algorithmic foundations of differential privacy. Foundations and Trends\u00ae in Theoretical Computer Science, Vol. 9, 3--4 (2014), 211--407."},{"key":"e_1_3_2_2_11_1","volume-title":"Secure multi-party computation. Manuscript. Preliminary version","author":"Goldreich Oded","year":"1998","unstructured":"Oded Goldreich . 1998. Secure multi-party computation. Manuscript. Preliminary version , Vol. 78 ( 1998 ), 110. Oded Goldreich. 1998. Secure multi-party computation. Manuscript. Preliminary version, Vol. 78 (1998), 110."},{"key":"e_1_3_2_2_12_1","volume-title":"Wortman Vaughan (Eds.)","volume":"34","author":"Han Yuxuan","year":"2021","unstructured":"Yuxuan Han , Zhipeng Liang , Yang Wang , and Jiheng Zhang . 2021 . Generalized Linear Bandits with Local Differential Privacy. In Advances in Neural Information Processing Systems, M. Ranzato, A. Beygelzimer, Y. Dauphin, P.S. Liang, and J . Wortman Vaughan (Eds.) , Vol. 34 . Curran Associates, Inc., 26511--26522. https:\/\/proceedings.neurips.cc\/paper\/ 2021\/file\/df0e09d6f25a15a815563df9827f48fa-Paper.pdf Yuxuan Han, Zhipeng Liang, Yang Wang, and Jiheng Zhang. 2021. Generalized Linear Bandits with Local Differential Privacy. In Advances in Neural Information Processing Systems, M. Ranzato, A. Beygelzimer, Y. Dauphin, P.S. Liang, and J. Wortman Vaughan (Eds.), Vol. 34. Curran Associates, Inc., 26511--26522. https:\/\/proceedings.neurips.cc\/paper\/2021\/file\/df0e09d6f25a15a815563df9827f48fa-Paper.pdf"},{"key":"e_1_3_2_2_13_1","volume-title":"Privacy-Preserving Contextual Bandits. CoRR","author":"Hannun Awni Y.","year":"2019","unstructured":"Awni Y. Hannun , Brian Knott , Shubho Sengupta , and Laurens van der Maaten . 2019. Privacy-Preserving Contextual Bandits. CoRR , Vol. abs\/ 1910 .05299 ( 2019 ). [arXiv]1910.05299 http:\/\/arxiv.org\/abs\/1910.05299 Awni Y. Hannun, Brian Knott, Shubho Sengupta, and Laurens van der Maaten. 2019. Privacy-Preserving Contextual Bandits. CoRR, Vol. abs\/1910.05299 (2019). [arXiv]1910.05299 http:\/\/arxiv.org\/abs\/1910.05299"},{"key":"e_1_3_2_2_14_1","volume-title":"Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption. arXiv preprint arXiv:1711.10677","author":"Hardy Stephen","year":"2017","unstructured":"Stephen Hardy , Wilko Henecka , Hamish Ivey-Law , Richard Nock , Giorgio Patrini , Guillaume Smith , and Brian Thorne . 2017. Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption. arXiv preprint arXiv:1711.10677 ( 2017 ). Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Richard Nock, Giorgio Patrini, Guillaume Smith, and Brian Thorne. 2017. Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption. arXiv preprint arXiv:1711.10677 (2017)."},{"key":"e_1_3_2_2_15_1","volume-title":"Fast Matrix Factorization for Online Recommendation with Implicit Feedback. CoRR","author":"He Xiangnan","year":"2017","unstructured":"Xiangnan He , Hanwang Zhang , Min-Yen Kan , and Tat-Seng Chua . 2017. Fast Matrix Factorization for Online Recommendation with Implicit Feedback. CoRR , Vol. abs\/ 1708 .05024 ( 2017 ). showeprint[arXiv]1708.05024 http:\/\/arxiv.org\/abs\/1708.05024 Xiangnan He, Hanwang Zhang, Min-Yen Kan, and Tat-Seng Chua. 2017. Fast Matrix Factorization for Online Recommendation with Implicit Feedback. CoRR, Vol. abs\/1708.05024 (2017). showeprint[arXiv]1708.05024 http:\/\/arxiv.org\/abs\/1708.05024"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330765"},{"key":"e_1_3_2_2_17_1","volume-title":"Federated Linear Contextual Bandits. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021","author":"Huang Ruiquan","year":"2021","unstructured":"Ruiquan Huang , Weiqiang Wu , Jing Yang , and Cong Shen . 2021 . Federated Linear Contextual Bandits. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021 , NeurIPS 2021, December 6-14, 2021, virtual, Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, and Jennifer Wortman Vaughan (Eds.). 27057--27068. https:\/\/proceedings.neurips.cc\/paper\/2021\/hash\/e347c51419ffb23ca3fd5050202f9c3d-Abstract.html Ruiquan Huang, Weiqiang Wu, Jing Yang, and Cong Shen. 2021. Federated Linear Contextual Bandits. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, and Jennifer Wortman Vaughan (Eds.). 27057--27068. https:\/\/proceedings.neurips.cc\/paper\/2021\/hash\/e347c51419ffb23ca3fd5050202f9c3d-Abstract.html"},{"key":"e_1_3_2_2_18_1","unstructured":"Criteo AI Labs. 2014. https:\/\/labs.criteo.com\/2014\/02\/kaggle-display-advertising-challenge-dataset\/  Criteo AI Labs. 2014. https:\/\/labs.criteo.com\/2014\/02\/kaggle-display-advertising-challenge-dataset\/"},{"volume-title":"Bandit algorithms","author":"Lattimore Tor","key":"e_1_3_2_2_19_1","unstructured":"Tor Lattimore and Csaba Szepesv\u00e1ri . 2020. Bandit algorithms . Cambridge University Press . Tor Lattimore and Csaba Szepesv\u00e1ri. 2020. Bandit algorithms. Cambridge University Press."},{"key":"e_1_3_2_2_20_1","volume-title":"Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits. In International Conference on Artificial Intelligence and Statistics, AISTATS 2022","volume":"6553","author":"Li Chuanhao","year":"2022","unstructured":"Chuanhao Li and Hongning Wang . 2022 . Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits. In International Conference on Artificial Intelligence and Statistics, AISTATS 2022 , 28-30 March 2022, Virtual Event (Proceedings of Machine Learning Research , Vol. 151), Gustau Camps-Valls, Francisco J. R. Ruiz, and Isabel Valera (Eds.). PMLR, 6529-- 6553 . https:\/\/proceedings.mlr.press\/v151\/li22e.html Chuanhao Li and Hongning Wang. 2022. Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits. In International Conference on Artificial Intelligence and Statistics, AISTATS 2022, 28-30 March 2022, Virtual Event (Proceedings of Machine Learning Research, Vol. 151), Gustau Camps-Valls, Francisco J. R. Ruiz, and Isabel Valera (Eds.). PMLR, 6529--6553. https:\/\/proceedings.mlr.press\/v151\/li22e.html"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772758"},{"key":"e_1_3_2_2_22_1","volume-title":"International Conference on Machine Learning. PMLR","author":"Li Lihong","year":"2017","unstructured":"Lihong Li , Yu Lu , and Dengyong Zhou . 2017 . Provably optimal algorithms for generalized linear contextual bandits . In International Conference on Machine Learning. PMLR , 2071--2080. Lihong Li, Yu Lu, and Dengyong Zhou. 2017. Provably optimal algorithms for generalized linear contextual bandits. In International Conference on Machine Learning. PMLR, 2071--2080."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT44484.2020.9174297"},{"key":"e_1_3_2_2_24_1","volume-title":"Chawathe","author":"Liang Gang","year":"2004","unstructured":"Gang Liang and Sudarshan S . Chawathe . 2004 . Privacy-Preserving Inter-database Operations. In Intelligence and Security Informatics . Gang Liang and Sudarshan S. Chawathe. 2004. Privacy-Preserving Inter-database Operations. In Intelligence and Security Informatics."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.09.005"},{"key":"e_1_3_2_2_26_1","volume-title":"Privacy-Preserving Bandits. In Proceedings of Machine Learning and Systems 2020","author":"Malekzadeh Mohammad","year":"2020","unstructured":"Mohammad Malekzadeh , Dimitrios Athanasakis , Hamed Haddadi , and Benjamin Livshits . 2020 . Privacy-Preserving Bandits. In Proceedings of Machine Learning and Systems 2020 , MLSys 2020, Austin, TX, USA , March 2-4, 2020, Inderjit S. Dhillon, Dimitris S. Papailiopoulos, and Vivienne Sze (Eds.). mlsys.org. https:\/\/proceedings.mlsys.org\/book\/310.pdf Mohammad Malekzadeh, Dimitrios Athanasakis, Hamed Haddadi, and Benjamin Livshits. 2020. Privacy-Preserving Bandits. In Proceedings of Machine Learning and Systems 2020, MLSys 2020, Austin, TX, USA, March 2-4, 2020, Inderjit S. Dhillon, Dimitris S. Papailiopoulos, and Vivienne Sze (Eds.). mlsys.org. https:\/\/proceedings.mlsys.org\/book\/310.pdf"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532031"},{"key":"e_1_3_2_2_28_1","volume-title":"Phasing: Private Set Intersection Using Permutation-based Hashing. In USENIX Security Symposium.","author":"Pinkas Benny","year":"2015","unstructured":"Benny Pinkas , T. Schneider , Gil Segev , and Michael Zohner . 2015 . Phasing: Private Set Intersection Using Permutation-based Hashing. In USENIX Security Symposium. Benny Pinkas, T. Schneider, Gil Segev, and Michael Zohner. 2015. Phasing: Private Set Intersection Using Permutation-based Hashing. In USENIX Security Symposium."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3501817"},{"key":"e_1_3_2_2_30_1","volume-title":"Pavlos Papadopoulos, Tom Titcombe, Abbas Ismail, Tudor Cebere, Robert Sandmann, Robin Roehm, and Michael A. Hoeh.","author":"Romanini Daniele","year":"2021","unstructured":"Daniele Romanini , Adam James Hall , Pavlos Papadopoulos, Tom Titcombe, Abbas Ismail, Tudor Cebere, Robert Sandmann, Robin Roehm, and Michael A. Hoeh. 2021 . PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN. CoRR , Vol. abs\/ 2104 .00489 (2021). showeprint[arXiv]2104.00489 https:\/\/arxiv.org\/abs\/2104.00489 Daniele Romanini, Adam James Hall, Pavlos Papadopoulos, Tom Titcombe, Abbas Ismail, Tudor Cebere, Robert Sandmann, Robin Roehm, and Michael A. Hoeh. 2021. PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN. CoRR, Vol. abs\/2104.00489 (2021). showeprint[arXiv]2104.00489 https:\/\/arxiv.org\/abs\/2104.00489"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2566486.2567978"},{"key":"e_1_3_2_2_32_1","volume-title":"Differentially Private Contextual Linear Bandits. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018","author":"Shariff Roshan","year":"2018","unstructured":"Roshan Shariff and Or Sheffet . 2018 . Differentially Private Contextual Linear Bandits. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018 , NeurIPS 2018, December 3-8, 2018, Montr\u00e9al, Canada, Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicol\u00f2 Cesa-Bianchi, and Roman Garnett (Eds.). 4301--4311. https:\/\/proceedings.neurips.cc\/paper\/2018\/hash\/a1d7311f2a312426d710e1c617fcbc8c-Abstract.html Roshan Shariff and Or Sheffet. 2018. Differentially Private Contextual Linear Bandits. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montr\u00e9al, Canada, Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicol\u00f2 Cesa-Bianchi, and Roman Garnett (Eds.). 4301--4311. https:\/\/proceedings.neurips.cc\/paper\/2018\/hash\/a1d7311f2a312426d710e1c617fcbc8c-Abstract.html"},{"key":"e_1_3_2_2_33_1","volume-title":"International Conference on Artificial Intelligence and Statistics. PMLR, 2917--2925","author":"Shi Chengshuai","year":"2021","unstructured":"Chengshuai Shi , Cong Shen , and Jing Yang . 2021 a. Federated multi-armed bandits with personalization . In International Conference on Artificial Intelligence and Statistics. PMLR, 2917--2925 . Chengshuai Shi, Cong Shen, and Jing Yang. 2021a. Federated multi-armed bandits with personalization. In International Conference on Artificial Intelligence and Statistics. PMLR, 2917--2925."},{"key":"e_1_3_2_2_34_1","volume-title":"Federated Multi-armed Bandits with Personalization. In The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021","volume":"2925","author":"Shi Chengshuai","year":"2021","unstructured":"Chengshuai Shi , Cong Shen , and Jing Yang . 2021 b. Federated Multi-armed Bandits with Personalization. In The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021 , April 13-15, 2021, Virtual Event (Proceedings of Machine Learning Research , Vol. 130), Arindam Banerjee and Kenji Fukumizu (Eds.). PMLR, 2917-- 2925 . http:\/\/proceedings.mlr.press\/v130\/shi21c.html Chengshuai Shi, Cong Shen, and Jing Yang. 2021b. Federated Multi-armed Bandits with Personalization. In The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event (Proceedings of Machine Learning Research, Vol. 130), Arindam Banerjee and Kenji Fukumizu (Eds.). PMLR, 2917--2925. http:\/\/proceedings.mlr.press\/v130\/shi21c.html"},{"key":"e_1_3_2_2_35_1","volume-title":"Foundations and Trends\u00ae in Machine Learning","volume":"12","author":"Aleksandrs","year":"2019","unstructured":"Aleksandrs Slivkins et al. 2019. Introduction to multi-armed bandits . Foundations and Trends\u00ae in Machine Learning , Vol. 12 , 1--2 ( 2019 ), 1--286. Aleksandrs Slivkins et al. 2019. Introduction to multi-armed bandits. Foundations and Trends\u00ae in Machine Learning, Vol. 12, 1--2 (2019), 1--286."},{"key":"e_1_3_2_2_36_1","volume-title":"Murphy","author":"Tewari Ambuj","year":"2017","unstructured":"Ambuj Tewari and Susan A . Murphy . 2017 . From Ads to Interventions : Contextual Bandits in Mobile Health. In Mobile Health - Sensors, Analytic Methods, and Applications, James M. Rehg, Susan A. Murphy, and Santosh Kumar (Eds.). Springer , 495--517. https:\/\/doi.org\/10.1007\/978-3-319-51394-2_25 10.1007\/978-3-319-51394-2_25 Ambuj Tewari and Susan A. Murphy. 2017. From Ads to Interventions: Contextual Bandits in Mobile Health. In Mobile Health - Sensors, Analytic Methods, and Applications, James M. Rehg, Susan A. Murphy, and Santosh Kumar (Eds.). Springer, 495--517. https:\/\/doi.org\/10.1007\/978-3-319-51394-2_25"},{"volume-title":"High-dimensional statistics: A non-asymptotic viewpoint","author":"Wainwright Martin J","key":"e_1_3_2_2_37_1","unstructured":"Martin J Wainwright . 2019. High-dimensional statistics: A non-asymptotic viewpoint . Vol. 48 . Cambridge University Press . Martin J Wainwright. 2019. High-dimensional statistics: A non-asymptotic viewpoint. Vol. 48. Cambridge University Press."},{"key":"e_1_3_2_2_38_1","volume-title":"Vertical Federated Learning: Challenges, Methodologies and Experiments. CoRR","author":"Wei Kang","year":"2022","unstructured":"Kang Wei , Jun Li , Chuan Ma , Ming Ding , Sha Wei , Fan Wu , Guihai Chen , and Thilina Ranbaduge . 2022. Vertical Federated Learning: Challenges, Methodologies and Experiments. CoRR , Vol. abs\/ 2202 .04309 ( 2022 ). showeprint[arXiv]2202.04309 https:\/\/arxiv.org\/abs\/2202.04309 Kang Wei, Jun Li, Chuan Ma, Ming Ding, Sha Wei, Fan Wu, Guihai Chen, and Thilina Ranbaduge. 2022. Vertical Federated Learning: Challenges, Methodologies and Experiments. CoRR, Vol. abs\/2202.04309 (2022). showeprint[arXiv]2202.04309 https:\/\/arxiv.org\/abs\/2202.04309"},{"key":"e_1_3_2_2_39_1","volume-title":"Privacy preserving vertical federated learning for tree-based models. arXiv preprint arXiv:2008.06170","author":"Wu Yuncheng","year":"2020","unstructured":"Yuncheng Wu , Shaofeng Cai , Xiaokui Xiao , Gang Chen , and Beng Chin Ooi . 2020. Privacy preserving vertical federated learning for tree-based models. arXiv preprint arXiv:2008.06170 ( 2020 ). Yuncheng Wu, Shaofeng Cai, Xiaokui Xiao, Gang Chen, and Beng Chin Ooi. 2020. Privacy preserving vertical federated learning for tree-based models. arXiv preprint arXiv:2008.06170 (2020)."},{"key":"e_1_3_2_2_40_1","volume-title":"Locally Differentially Private (Contextual) Bandits Learning. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020","author":"Zheng Kai","year":"2020","unstructured":"Kai Zheng , Tianle Cai , Weiran Huang , Zhenguo Li , and Liwei Wang . 2020 . Locally Differentially Private (Contextual) Bandits Learning. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020 , NeurIPS 2020, December 6-12, 2020, virtual, Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin (Eds.). https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/908c9a564a86426585b29f5335b619bc-Abstract.html Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, and Liwei Wang. 2020. Locally Differentially Private (Contextual) Bandits Learning. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin (Eds.). https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/908c9a564a86426585b29f5335b619bc-Abstract.html"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3410220.3453919"}],"event":{"name":"KDD '23: The 29th 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":"Long Beach CA USA","acronym":"KDD '23"},"container-title":["Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3580305.3599475","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3580305.3599475","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:37Z","timestamp":1750178257000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3580305.3599475"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,4]]},"references-count":41,"alternative-id":["10.1145\/3580305.3599475","10.1145\/3580305"],"URL":"https:\/\/doi.org\/10.1145\/3580305.3599475","relation":{},"subject":[],"published":{"date-parts":[[2023,8,4]]},"assertion":[{"value":"2023-08-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}