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We study identifying user clusters in contextual multi-armed bandits (MAB).
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Josip Djolonga, Andreas Krause, and Volkan Cevher. 2013 · 2013
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Online clustering of contextual cascading bandits. In Thirty-Second AAAI Conference on Artificial Intelligence
Shuai Li and Shengyu Zhang. 2018 · 2018
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Unlearn what you have learned: Adaptive crowd teaching with exponentially decayed memory learners. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 2817–2826
Yao Zhou, Arun Reddy Nelakurthi, and Jingrui He. 2018 · 2018
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Balanced linear contextual bandits. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 33. 3445–3453
Maria Dimakopoulou, Zhengyuan Zhou, Susan Athey, and Guido Imbens. 2019 · 2019
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Improved algorithm on online clustering of bandits. In Proceedings of the 28th International Joint Conference on Artificial Intelligence . AAAI Press, 2923–2929
Shuai Li, Wei Chen, Shuai Li, and Kwong-Sak Leung. 2019 · 2019
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Claudio Gentile, Shuai Li, and Giovanni Zappella. 2014 · 2014
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Daniel Schall. 2014 · 2014
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The movielens datasets: History and context
F Maxwell Harper and Joseph A Konstan. 2015 · 2015
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Personalized recommendation via parameter-free contextual bandits. In Proceedings of the 38th international ACM SIGIR conference on research and development in information retrieval . 323–332
Liang Tang, Yexi Jiang, Lei Li, Chunqiu Zeng, and Tao Li. 2015 · 2015
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Collaborative filtering bandits. In Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval . 539–548
Shuai Li, Alexandros Karatzoglou, and Claudio Gentile. 2016 · 2016
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Contextual bandits in a collaborative environment. In Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval . 529–538
Qingyun Wu, Huazheng Wang, Quanquan Gu, and Hongning Wang. 2016 · 2016
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On context-dependent clustering of bandits. In Proceedings of the 34th International Conference on Machine Learning-Volume 70 . JMLR. org, 1253–1262
Claudio Gentile, Shuai Li, Purushottam Kar, Alexandros Karatzoglou, Giovanni Zappella, and Evans Etrue. 2017 · 2017
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Ban Yikun, Liu Xin, Huang Ling, Duan Yitao, Liu Xue, and Xu Wei. 2019 · 2019
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Generic Outlier Detection in Multi-Armed Bandit. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 913–923
Yikun Ban and Jingrui He. 2020 · 2020
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Online decision making with high-dimensional covariates
Hamsa Bastani and Mohsen Bayati. 2020 · 2020
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Local Motif Clustering on Time-Evolving Graphs. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 390–400
Dongqi Fu, Dawei Zhou, and Jingrui He. 2020 · 2020
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User Recommendation in Content Curation Platforms. In Proceedings of the 13th International Conference on Web Search and Data Mining . 627–635
Jianling Wang, Ziwei Zhu, and James Caverlee. 2020 · 2020
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Crowd Teaching with Imperfect Labels. In Proceedings of The Web Conference 2020 . 110–121
Yao Zhou, Arun Reddy Nelakurthi, Ross Maciejewski, Wei Fan, and Jingrui He. 2020 · 2020
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Convolutional neural bandit: Provable algorithm for visual-aware advertising
Yikun Ban and Jingrui He. 2021 · 2021
Closest in time.
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits
Yikun Ban, Yuchen Yan, Arindam Banerjee, and Jingrui He. 2021b · 2021
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High-Order Structure Exploration on Massive Graphs: A Local Graph Clustering Perspective
Dawei Zhou, Si Zhang, Mehmet Yigit Yildirim, Scott Alcorn, Hanghang Tong, Hasan Davulcu, and Jingrui He. 2021 · 2021
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Neural Bandit with Arm Group Graph. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 1379–1389
Yunzhe Qi, Yikun Ban, and Jingrui He. 2022 · 2022
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