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We propose a novel algorithm for sequential matrix completion in a recommender system setting, where the $(i,j)$th entry of the matrix corresponds to a user $i$'s rating of product $j$.
Asymptotically efficient adaptive allocation rules
Lai, Tze Leung and Robbins, Herbert · 1985
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On the Gittins index for multiarmed bandits
Weber, Richard et al · 1992
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Eigentaste: A constant time collaborative filtering algorithm
Goldberg, Ken, Roeder, Theresa, Gupta, Dhruv, and Perkins, Chris · 2001
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Exact matrix completion via convex optimization
Candès, Emmanuel J and Recht, Benjamin · 2009
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Low-rank matrix completion with noisy observations: a quantitative comparison
Keshavan, Raghunandan H, Montanari, Andrea, and Oh, Sewoong · 2009
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Matrix completion from a few entries
Keshavan, Raghunandan H, Oh, Sewoong, and Montanari, Andrea · 2009
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Matrix completion with noise
Candès, Emmanuel J and Plan, Yaniv · 2010
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A note on efficient conditional simulation of gaussian distributions
Doucet, A · 2010
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A contextual-bandit approach to personalized news article recommendation
Li, Lihong, Chu, Wei, Langford, John, and Schapire, Robert E · 2010
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Linear bandits in high dimension and recommendation systems
Deshpande, Yash and Montanari, Andrea · 2012
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Thompson sampling: An asymptotically optimal finite-time analysis
Kaufmann, Emilie, Korda, Nathaniel, and Munos, Rémi · 2012
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Adadelta: an adaptive learning rate method
Zeiler, Matthew D · 2012
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Agrawal, Shipra and Goyal, Navin · 2013
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Stochastic variational inference
Hoffman, Matthew D, Blei, David M, Wang, Chong, and Paisley, John · 2013
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Noisy low-rank matrix completion with general sampling distribution
Klopp, Olga et al · 2014
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High-dimensional covariance matrix estimation with missing observations
Lounici, Karim et al · 2014
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Efficient Thompson sampling for online matrix-factorization recommendation
Kawale, Jaya, Bui, Hung H, Kveton, Branislav, Tran-Thanh, Long, and Chawla, Sanjay · 2015
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The algebraic combinatorial approach for low-rank matrix completion
Király, Franz J, Theran, Louis, and Tomioka, Ryota · 2015
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Stochastic gradient variational Bayes for gamma approximating distributions
Knowles, David A · 2015
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http://grouplens.org/datasets/movielens/
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Kingma, Diederik P and Welling, Max · 2013
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Fixed-form variational posterior approximation through stochastic linear regression
Salimans, Tim, Knowles, David A, et al · 2013
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Interactive collaborative filtering
Zhao, Xiaoxue, Zhang, Weinan, and Wang, Jun · 2013
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A latent source model for online collaborative filtering
Bresler, Guy, Chen, George H, and Shah, Devavrat · 2014
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Learning to optimize via posterior sampling
Russo, Daniel and Van Roy, Benjamin
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Learning to optimize via information-directed sampling
Russo, Daniel and Van Roy, Benjamin
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Movielens · 2016
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Variational inference: A review for statisticians
Blei, David M, Kucukelbir, Alp, and McAuliffe, Jon D · 2016
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Collaborative filtering bandits
Li, Shuai, Karatzoglou, Alexandros, and Gentile, Claudio · 2016
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A characterization of deterministic sampling patterns for low-rank matrix completion
Pimentel-Alarcón, Daniel L, Boston, Nigel, and Nowak, Robert D · 2016
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