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A common problem in machine learning is to rank a set of n items based on pairwise comparisons.
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Eyal Even-Dar, Shie Mannor and Yishay Mansour · 2006
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Nir Ailon · 2011
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Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer and Peter Stone · 2012
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Matthew. Salganik and Karen E.. Levy · 2015
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“Simple, robust and optimal ranking from pairwise comparisons”
Nihar. Shah and Martin. Wainwright · 2015
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“Online rank elicitation for Plackett-Luce: A dueling bandits approach”
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“Recommender systems: The textbook”
Charu. Aggarwal · 2016
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“Active ranking from pairwise comparisons and when parametric assumptions don’t help”
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Bruce Hajek, Sewoong Oh and Jiaming Xu · 2014
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Yuan Zhou, Xi Chen and Jian Li · 2014
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“Mémoire sur les élections au scrutin”
Jean De
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Reinhard Heckel, Nihar. Shah, Kannan Ramchandran and Martin. Wainwright · 2016
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“Estimation from pairwise comparisons: Sharp minimax bounds with topology dependence”
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“Stochastically transitive models for pairwise comparisons: Statistical and computational issues”
Nihar. Shah, Sivaraman Balakrishnan, Adityanand Guntuboyina and Martin. Wainwright · 2016
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“Nearly instance optimal sample complexity bounds for top-k arm selection”
Lijie Chen, Jian Li and Mingda Qiao · 2017
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“The simulator: Understanding adaptive sampling in the moderate-confidence regime”
M. Simchowitz, K. Jamieson and B. Recht · 2017
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