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Classical multi-armed bandit problems use the expected value of an arm as a metric to evaluate its goodness.
Risk-aware multi-armed bandits using conditional value-at-risk
Ravi Kumar Kolla, Krishna Jagannathan, et al · 1901
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On some robust estimates of location
Peter J Bickel et al · 1965
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Coherent measures of risk
Philippe Artzner, Freddy Delbaen, Jean-Marc Eber, and David Heath · 1999
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Financial risk and heavy tails
Brendan O Bradley and Murad S Taqqu · 2003
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Deviation inequalities for an estimator of the conditional value-at-risk
Ying Wang and Fuqing Gao · 2010
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Best arm identification in multi-armed bandits
Jean-Yves Audibert and Sébastien Bubeck · 2010
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Regret analysis of stochastic and nonstochastic multi-armed bandit problems
Sébastien Bubeck, Nicolo Cesa-Bianchi, et al · 2012
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Risk-aversion in multi-armed bandits
Amir Sani, Alessandro Lazaric, and Rémi Munos · 2012
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Bandits with heavy tail
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Deterministic sequencing of exploration and exploitation for multi-armed bandit problems
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Concentration inequalities: A nonasymptotic theory of independence
Stéphane Boucheron, Gábor Lugosi, and Pascal Massart · 2013
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Concentration bounds for empirical conditional value-at-risk: The unbounded case
Ravi Kumar Kolla, LA Prashanth, Sanjay P Bhat, and Krishna Jagannathan
Exploration vs exploitation vs safety: Risk-aware multi-armed bandits
Nicolas Galichet, Michele Sebag, and Olivier Teytaud · 2013
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Pure exploration for max-quantile bandits
Yahel David and Nahum Shimkin · 2016
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Bandit algorithms
Tor Lattimore and Csaba Szepesvári · 2018
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Pure exploration of multi-armed bandits with heavy-tailed payoffs
Xiaotian Yu, Han Shao, Michael R Lyu, and Irwin King · 2018
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Pac bandits with risk constraints
Yahel David, Balázs Szörényi, Mohammad Ghavamzadeh, Shie Mannor, and Nahum Shimkin · 2018
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