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We study a recommender system for quantum data using the linear contextual bandit framework.
Bandit processes and dynamic allocation indices
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T. L. Lai · 1987
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Restless bandits: Activity allocation in a changing world
P. Whittle · 1988
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N. Abe, A. W. Biermann, and P. M. Long · 2003
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Using confidence bounds for exploitation-exploration trade-offs
P. Auer · 2003
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P. Auer, N. Cesa-Bianchi, Y. Freund, and R. E. Schapire · 2003
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D. Varsha, T. Hayes, and S.Kakade · 2008
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A contextual-bandit approach to personalized news article recommendation
L. Li, W. Chu, J. Langford, and R. E. Schapire · 2010
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Linearly parameterized bandits
P. Rusmevichientong and J. N. Tsitsiklis · 2010
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Contextual bandits with linear payoff functions
W. Chu, L. Li, L. Reyzin, and R. E. Schapire · 2011
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Improved algorithms for linear stochastic bandits
Y. Abbasi-Yadkori, D. Pál, and Cs. Szepesvári · 2011
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Multi-armed bandit allocation indices
J. Gittins, K. Glazebrook, and R. Weber · 2011
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Automatic ad format selection via contextual bandits
L. Tang, R. Rosales, A. Singh, and D. Agarwal · 2013
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Thompson sampling for contextual bandits with linear payoffs
S. Agrawal and N. Goyal · 2013
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Eluder dimension and the sample complexity of optimistic exploration
D. Russo and B. Van Roy · 2013
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Quantum partially observable markov decision processes
J. Barry, D.T. Barry, and S. Aaronson · 2014
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A variational eigenvalue solver on a photonic quantum processor
A. Peruzzo, J. McClean, Jarrod, P. Shadbolt, M. Yung, X. Zhou, P. J. Love, A. Aspuru-Guzik, and J. L. O’brien · 2014
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Bounded regret for finite-armed structured bandits
T. Lattimore and R. Munos · 2014
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The netflix recommender system: Algorithms, business value, and innovation
C. A. Gomez-Uribe and N. Hunt · 2016
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Quantum recommendation systems
I. Kerenidis and A. Prakash · 2016
A quantum-inspired classical algorithm for recommendation systems
E. Tang · 2019
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Bandit algorithms
T. Lattimore and C. Szepesvári · 2020
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Survey on applications of multi-armed and contextual bandits
D. Bouneffouf, I. Rish, and C. Aggarwal · 2020
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Feature-based dynamic pricing
M. Cohen, I. Lobel, and R. Paes Leme · 2020
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Quantum bandits
B. Casalé, G. Di Molfetta, H. Kadri, and L. Ralaivola · 2020
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Predicting many properties of a quantum system from very few measurements
H. Huang, R. Kueng, and J. Preskill · 2020
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Quantum exploration algorithms for multi-armed bandits
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One-dimensional symmetry protected topological phases and their transitions
R. Verresen, R. Moessner, and F. Pollmann · 2017
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Minimal exploration in structured stochastic bandits
R. Combes, S. Magureanu, and A. Proutiere · 2017
Cited alongside, same era.
Contextual bandits for adapting treatment in a mouse model of de novo carcinogenesis
A. Durand, C. Achilleos, D. Iacovides, K. Strati, G. D. Mitsis, and J. Pineau · 2018
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Explore, exploit, and explain: personalizing explainable recommendations with bandits
J. McInerney, B. Lacker, S. Hansen, K. Higley, H. Bouchard, A. Gruson, and R. Mehrotra · 2018
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Shadow tomography of quantum states
S. Aaronson · 2018
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Efficient contextual bandits in non-stationary worlds
H. Luo, C. Wei, Chen-Yu, A. Agarwal, and J. Langford · 2018
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D. Wang, X. You, T. Li, and A. Childs · 2021
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Optimal policies for quantum markov decision processes
M. Ying, Y. Feng, and S. Ying · 2021
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Quantum multi-armed bandits and stochastic linear bandits enjoy logarithmic regrets
Z. Wan, Z. Zhang, T. Li, J. Zhang, and X. Sun · 2022
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Quantum bandit with amplitude amplification exploration in an adversarial environment
B. Cho, Y. Xiao, P. Hui, and D. Dong · 2022
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Multi-armed quantum bandits: Exploration versus exploitation when learning properties of quantum states
J. Lumbreras, E. Haapasalo, and M. Tomamichel · 2022
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Noisy intermediate-scale quantum algorithms
K. Bharti, A. Cervera-Lierta, T.H. Kyaw, T. Haug, S. Alperin-Lea, A. Anand, M. Degroote, H. Heimonen, J. S. Kottmann, T. Menke, W. Mok, S. Sim, L. Kwek, and A. Aspuru-Guzik · 2022
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Generalization in quantum machine learning from few training data
M. C. Caro, H. Huang, M. Cerezo, K. Sharma, A. Sornborger, L. Cincio, and P. J. Coles · 2022
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