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Bandit algorithms have various application in safety-critical systems, where it is important to respect the system constraints that rely on the bandit's unknown parameters at every round.
Finite-time analysis of the multiarmed bandit problem
Peter Auer, Nicolò Cesa-Bianchi, and Paul Fischer · 2002
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Stochastic linear optimization under bandit feedback
Varsha Dani, Thomas P Hayes, and Sham M Kakade · 2008
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Exploration–exploitation tradeoff using variance estimates in multi-armed bandits
Jean-Yves Audibert, Rémi Munos, and Csaba Szepesvári · 2009
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Linearly parameterized bandits
Paat Rusmevichientong and John N. Tsitsiklis · 2010
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Parametric bandits: The generalized linear case
Sarah Filippi, Olivier Cappe, Aurélien Garivier, and Csaba Szepesvári · 2010
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Gaussian process optimization in the bandit setting: no regret and experimental design
Niranjan Srinivas, Andreas Krause, Sham Kakade, and Matthias Seeger · 2010
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Improved algorithms for linear stochastic bandits
Yasin Abbasi-Yadkori, Dávid Pál, and Csaba Szepesvári · 2011
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Contextual bandits with linear payoff functions
Wei Chu, Lihong Li, Lev Reyzin, and Robert Schapire · 2011
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Guaranteed safe online learning of a bounded system
J. H. Gillulay and C. J. Tomlin · 2011
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Safe exploration in markov decision processes
Teodor Mihai Moldovan and Pieter Abbeel · 2012
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Bandits with knapsacks
A. Badanidiyuru, R. Kleinberg, and A. Slivkins · 2013
Cited alongside, same era.
Provably safe and robust learning-based model predictive control
Anil Aswani, Humberto Gonzalez, S Shankar Sastry, and Claire Tomlin · 2013
Cited alongside, same era.
Learning to optimize via posterior sampling
Daniel Russo and Benjamin Van Roy · 2014
Cited alongside, same era.
Resourceful contextual bandits
Ashwinkumar Badanidiyuru, John Langford, and Aleksandrs Slivkins · 2014
Cited alongside, same era.
Reachability-based safe learning with gaussian processes
A. K. Akametalu, J. F. Fisac, J. H. Gillula, S. Kaynama, M. N. Zeilinger, and C. J. Tomlin · 2014
Cited alongside, same era.
Algorithms with logarithmic or sublinear regret for constrained contextual bandits
Huasen Wu, R. Srikant, Xin Liu, and Chong Jiang · 2015
Cited alongside, same era.
Linear contextual bandits with knapsacks
Shipra Agrawal and Nikhil Devanur · 2016
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Conservative bandits
Yifan Wu, Roshan Shariff, Tor Lattimore, and Csaba Szepesvári · 2016
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Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics
Felix Berkenkamp, Andreas Krause, and Angela P Schoellig · 2016
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Robust constrained learning-based nmpc enabling reliable mobile robot path tracking
Chris J Ostafew, Angela P Schoellig, and Timothy D Barfoot · 2016
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Provably optimal algorithms for generalized linear contextual bandits
Lihong Li, Yu Lu, and Dengyong Zhou · 2017
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Conservative contextual linear bandits
Abbas Kazerouni, Mohammad Ghavamzadeh, Yasin Abbasi, and Benjamin Van Roy · 2017
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Safe exploration for active learning with gaussian processes
Jens Schreiter, Duy Nguyen-Tuong, Mona Eberts, Bastian Bischoff, Heiner Markert, and Marc Toussaint · 2015
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Safe exploration for optimization with gaussian processes
Yanan Sui, Alkis Gotovos, Joel W. Burdick, and Andreas Krause · 2015
Cited alongside, same era.
An introduction to matrix concentration inequalities
Joel A Tropp et al · 2015
Cited alongside, same era.
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Constrained policy optimization
Joshua Achiam, David Held, Aviv Tamar, and Pieter Abbeel · 2017
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Stagewise safe bayesian optimization with gaussian processes
Yanan Sui, Joel Burdick, Yisong Yue, et al · 2018
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Safe convex learning under uncertain constraints
Ilnura Usmanova, Andreas Krause, and Maryam Kamgarpour · 2019
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