暂无分享,去创建一个
[1] Peter S. Fader,et al. Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments , 2016, Mark. Sci..
[2] Donald A. Berry,et al. Bandit Problems: Sequential Allocation of Experiments. , 1986 .
[3] Osamu Watanabe,et al. Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms , 1999, Data Mining and Knowledge Discovery.
[4] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[5] Sampath Kannan,et al. A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem , 2018, NeurIPS.
[6] Nikita Mishra,et al. (Nearly) Optimal Differentially Private Stochastic Multi-Arm Bandits , 2015, UAI.
[7] Cynthia Dwork,et al. Calibrating Noise to Sensitivity in Private Data Analysis , 2006, TCC.
[8] Csaba Szepesvári,et al. Empirical Bernstein stopping , 2008, ICML '08.
[9] Roshan Shariff,et al. Differentially Private Contextual Linear Bandits , 2018, NeurIPS.
[10] Christos Dimitrakakis,et al. Algorithms for Differentially Private Multi-Armed Bandits , 2015, AAAI.
[11] Elaine Shi,et al. Private and Continual Release of Statistics , 2010, TSEC.
[12] Eric T. Bradlow,et al. Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments , 2016 .
[13] Stéphane Caron,et al. Mixing bandits: a recipe for improved cold-start recommendations in a social network , 2013, SNAKDD '13.
[14] Vishesh Karwa,et al. Finite Sample Differentially Private Confidence Intervals , 2017, ITCS.
[15] Vianney Perchet,et al. Bounded regret in stochastic multi-armed bandits , 2013, COLT.
[16] Peter Auer,et al. The Nonstochastic Multiarmed Bandit Problem , 2002, SIAM J. Comput..
[17] Nando de Freitas,et al. Portfolio Allocation for Bayesian Optimization , 2010, UAI.
[18] W. Hoeffding. Probability Inequalities for sums of Bounded Random Variables , 1963 .
[19] Thomas Steinke,et al. Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds , 2016, TCC.
[20] Zheng Wen,et al. Cascading Bandits: Learning to Rank in the Cascade Model , 2015, ICML.
[21] H. Robbins. Some aspects of the sequential design of experiments , 1952 .
[22] Martha White,et al. High-confidence error estimates for learned value functions , 2018, UAI.
[23] Richard M. Karp,et al. An Optimal Algorithm for Monte Carlo Estimation , 2000, SIAM J. Comput..
[24] Moni Naor,et al. Differential privacy under continual observation , 2010, STOC '10.
[25] Shie Mannor,et al. PAC Bounds for Multi-armed Bandit and Markov Decision Processes , 2002, COLT.
[26] T. L. Lai Andherbertrobbins. Asymptotically Efficient Adaptive Allocation Rules , 2022 .
[27] Adam D. Smith,et al. (Nearly) Optimal Algorithms for Private Online Learning in Full-information and Bandit Settings , 2013, NIPS.