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[1] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[2] Odalric-Ambrym Maillard. Self-normalization techniques for streaming confident regression , 2016 .
[3] Massimiliano Pontil,et al. Empirical Bernstein Bounds and Sample-Variance Penalization , 2009, COLT.
[4] Alan Fern,et al. Using trajectory data to improve bayesian optimization for reinforcement learning , 2014, J. Mach. Learn. Res..
[5] Nathan Srebro,et al. Explicit Approximations of the Gaussian Kernel , 2011, ArXiv.
[6] W. R. Thompson. ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES , 1933 .
[7] Alessandro Lazaric,et al. Linear Thompson Sampling Revisited , 2016, AISTATS.
[8] Jasper Snoek,et al. Practical Bayesian Optimization of Machine Learning Algorithms , 2012, NIPS.
[9] M. Abramowitz,et al. Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .
[10] Fabio Tozeto Ramos,et al. Bayesian Optimisation for informative continuous path planning , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[11] Csaba Szepesvári,et al. Improved Algorithms for Linear Stochastic Bandits , 2011, NIPS.
[12] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[13] Nello Cristianini,et al. Finite-Time Analysis of Kernelised Contextual Bandits , 2013, UAI.
[14] Andreas Krause,et al. Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting , 2009, IEEE Transactions on Information Theory.
[15] Nando de Freitas,et al. Active Preference Learning with Discrete Choice Data , 2007, NIPS.
[16] Wei Chu,et al. A contextual-bandit approach to personalized news article recommendation , 2010, WWW '10.
[17] Shipra Agrawal,et al. Thompson Sampling for Contextual Bandits with Linear Payoffs , 2012, ICML.
[18] Andreas Krause,et al. Contextual Gaussian Process Bandit Optimization , 2011, NIPS.
[19] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[20] Wei Chu,et al. Contextual Bandits with Linear Payoff Functions , 2011, AISTATS.
[21] Nando de Freitas,et al. Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-Parameters , 2014, ArXiv.
[22] S. Loustau. Penalized empirical risk minimization over Besov spaces , 2009 .
[23] Milton Abramowitz,et al. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables , 1964 .
[24] S. Canu,et al. M L ] 6 O ct 2 00 9 Functional learning through kernel , 2009 .