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We extend the model of stochastic bandits with adversarial corruption (Lykouriset al., 2018) to the stochastic linear optimization problem (Dani et al., 2008).
Tight regret bounds for infinite-armed linear contextual bandits
Li, Y., Wang, Y., and Zhou, Y. (2019) · 1905
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Some aspects of the sequential design of experiments
Robbins, H. (1952) · 1952
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Probability inequalities for sums of bounded random variables
Hoeffding, W. (1963) · 1963
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An optimal algorithm for stochastic and adversarial bandits
Zimmert, J. and Seldin, Y. (2018) · 1963
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Geometric algorithms and combinatorial optimization
Grtschel, M., Lovsz, L., and Schrijver, A. (1988) · 1988
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Geometric algorithms and algorithmic geometry
Lovász, L. (1991) · 1990
Cited alongside, same era.
Using confidence bounds for exploitation-exploration trade-offs
Auer, P. (2002) · 2002
Cited alongside, same era.
Stochastic linear optimization under bandit feedback
Dani, V., Hayes, T. P., and Kakade, S. M. (2008) · 2008
Cited alongside, same era.
Improved algorithms for linear stochastic bandits
Abbasi-Yadkori, Y., Pál, D., and Szepesvári, C. (2011) · 2011
Cited alongside, same era.
Contextual bandit algorithms with supervised learning guarantees
Beygelzimer, A., Langford, J., Li, L., Reyzin, L., and Schapire, R. (2011) · 2011
Cited alongside, same era.
The best of both worlds: stochastic and adversarial bandits
Bubeck, S. and Slivkins, A. (2012) · 2012
Later among the works it cites.
The end of optimism? An asymptotic analysis of finite-armed linear bandits
Lattimore, T. and Szepesvari, C. (2017) · 2017
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Stochastic bandits robust to adversarial corruptions
Lykouris, T., Mirrokni, V., and Paes Leme, R. (2018) · 2018
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Better algorithms for stochastic bandits with adversarial corruptions
Gupta, A., Koren, T., and Talwar, K. (2019) · 2019
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Corruption-tolerant bandit learning
Kapoor, S., Patel, K. K., and Kar, P. (2019) · 2019
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