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Computationally efficient contextual bandits are often based on estimating a predictive model of rewards given contexts and arms using past data.
Foster, D. J., Rakhlin, A., Simchi-Levi, D., and Xu, Y · 2010
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A contextual-bandit approach to personalized news article recommendation
Li, L., Chu, W., Langford, J., and Schapire, R. E · 2010
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Efficient optimal learning for contextual bandits
Dudik, M., Hsu, D., Kale, S., Karampatziakis, N., Langford, J., Reyzin, L., and Zhang, T · 2011
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Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: Ecole d’Eté de Probabilités de Saint-Flour XXXVIII-2008 , volume 2033
Koltchinskii, V · 2011
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Thompson sampling for contextual bandits with linear payoffs
Agrawal, S. and Goyal, N · 2013
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Taming the monster: A fast and simple algorithm for contextual bandits
Agarwal, A., Hsu, D., Kale, S., Langford, J., Li, L., and Schapire, R · 2014
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Misspecified linear bandits
Ghosh, A., Chowdhury, S. R., and Gopalan, A · 2017
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Practical contextual bandits with regression oracles
Foster, D. J., Agarwal, A., Dudík, M., Luo, H., and Schapire, R. E · 2018
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Beyond ucb: Optimal and efficient contextual bandits with regression oracles
Foster, D. J. and Rakhlin, A · 2020
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Tractable contextual bandits beyond realizability
Krishnamurthy, S. K., Hadad, V., and Athey, S · 2020
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Bandit algorithms
Lattimore, T. and Szepesvári, C · 2020
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Learning with good feature representations in bandits and in rl with a generative model
Lattimore, T., Szepesvari, C., and Weisz, G · 2020
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Efficient and robust algorithms for adversarial linear contextual bandits
Neu, G. and Olkhovskaya, J · 2020
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Model selection in contextual stochastic bandit problems
Pacchiano, A., Phan, M., Abbasi-Yadkori, Y., Rao, A., Zimmert, J., Lattimore, T., and Szepesvari, C · 2020
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Bypassing the monster: A faster and simpler optimal algorithm for contextual bandits under realizability
Simchi-Levi, D. and Xu, Y · 2020
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Upper counterfactual confidence bounds: a new optimism principle for contextual bandits
Xu, Y. and Zeevi, A · 2020
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Foster, D. J., Gentile, C., Mohri, M., and Zimmert, J
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