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This paper investigates the problem of regret minimization for multi-armed bandit (MAB) problems with local differential privacy (LDP) guarantee.
Differential privacy for multi-armed bandits: What is it and what is its cost?
Basu, D., Dimitrakakis, C., and Tossou, A. (2019) · 1905
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Malekzadeh, M., Athanasakis, D., Haddadi, H., and Livshits, B. (2019) · 1909
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Privacy-preserving multi-party contextual bandits
Hannun, A., Knott, B., Sengupta, S., and van der Maaten, L. (2019) · 1910
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Probability inequalities for sums of bounded random variables
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Bandit problems: Sequential allocation of experiments (Monographs on statistics and applied probability)
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Asymptotically efficient adaptive allocation rules
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Some inequalities for the kullback-leibler and χ \chi 2-distances in information theory and applications
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Finite-time analysis of the multiarmed bandit problem
Auer, P., Cesa-Bianchi, N., and Fischer, P. (2002) · 2002
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Private and continual release of statistics
Chan, T.-H. H., Shi, E., and Song, D. (2011) · 2011
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Differentially private data release for data mining
Mohammed, N., Chen, R., Fung, B., and Yu, P. S. (2011) · 2011
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Analysis of Thompson sampling for the multi-armed bandit problem
Agrawal, S. and Goyal, N. (2012) · 2012
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Elements of information theory
Cover, T. M. and Thomas, J. A. (2012) · 2012
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The algorithmic foundations of differential privacy
Dwork, C., Roth, A., et al. (2014) · 2014
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Private stochastic multi-arm bandits: From theory to practice
Mishra, N. and Thakurta, A. (2014) · 2014
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Calibrating noise to sensitivity in private data analysis
Dwork, C., McSherry, F., Nissim, K., and Smith, A. (2016) · 2016
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Algorithms for differentially private multi-armed bandits
Tossou, A. C. and Dimitrakakis, C. (2016) · 2016
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Achieving privacy in the adversarial multi-armed bandit
Tossou, A. C. Y. and Dimitrakakis, C. (2017) · 2017
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Corrupt bandits for preserving local privacy
Gajane, P., Urvoy, T., and Kaufmann, E. (2018) · 2018
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Bandit algorithms
Lattimore, T. and Szepesvári, C. (2018) · 2018
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Differentially private contextual linear bandits
Shariff, R. and Sheffet, O. (2018) · 2018
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Differentially private distributed optimization
Huang, Z., Mitra, S., and Vaidya, N. (2015) · 2015
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(Nearly) optimal differentially private stochastic multi-arm bandits
Mishra, N. and Thakurta, A. (2015) · 2015
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Differentially private, multi-agent multi-armed bandits
Tossou, A. C. and Dimitrakakis, C. (2015) · 2015
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Optimal differentially private finite armed stochastic bandit
Sajed, T. (2019) · 2019
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Privacy-preserving Q-learning with functional noise in continuous spaces
Wang, B. and Hegde, N. (2019) · 2019
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