Improved Learning Complexity in Combinatorial Pure Exploration Bandits
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Peter L. Bartlett | Alessandro Lazaric | Ronald Ortner | Mohammad Ghavamzadeh | Victor Gabillon | P. Bartlett | A. Lazaric | M. Ghavamzadeh | Victor Gabillon | R. Ortner
[1] Andrew W. Moore,et al. Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation , 1993, NIPS.
[2] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[3] Shie Mannor,et al. Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems , 2006, J. Mach. Learn. Res..
[4] H. Robbins. Some aspects of the sequential design of experiments , 1952 .
[5] Nicolò Cesa-Bianchi,et al. Combinatorial Bandits , 2012, COLT.
[6] Rémi Munos,et al. Pure Exploration in Multi-armed Bandits Problems , 2009, ALT.
[7] Peter Stone,et al. Efficient Selection of Multiple Bandit Arms: Theory and Practice , 2010, ICML.
[8] Rémi Munos,et al. Open Loop Optimistic Planning , 2010, COLT.
[9] Varun Grover,et al. Active learning in heteroscedastic noise , 2010, Theor. Comput. Sci..
[10] Warren B. Powell,et al. Information Collection on a Graph , 2011, Oper. Res..
[11] Alessandro Lazaric,et al. Multi-Bandit Best Arm Identification , 2011, NIPS.
[12] Ambuj Tewari,et al. PAC Subset Selection in Stochastic Multi-armed Bandits , 2012, ICML.
[13] Alessandro Lazaric,et al. Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence , 2012, NIPS.
[14] Tengyao Wang,et al. Multiple Identications in Multi-Armed Bandits , 2013 .
[15] Shivaram Kalyanakrishnan,et al. Information Complexity in Bandit Subset Selection , 2013, COLT.
[16] Sébastien Bubeck,et al. Multiple Identifications in Multi-Armed Bandits , 2012, ICML.
[17] Wei Chen,et al. Combinatorial multi-armed bandit: general framework, results and applications , 2013, ICML 2013.
[18] Rémi Munos,et al. From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning , 2014, Found. Trends Mach. Learn..
[19] Wei Chen,et al. Combinatorial Pure Exploration of Multi-Armed Bandits , 2014, NIPS.
[20] Alessandro Lazaric,et al. Best-Arm Identification in Linear Bandits , 2014, NIPS.
[21] Yifan Wu,et al. On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments , 2015, ICML.
[22] Zheng Wen,et al. Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits , 2014, AISTATS.
[23] Djallel Bouneffouf,et al. Finite-time analysis of the multi-armed bandit problem with known trend , 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).
[24] Stefano Ermon,et al. Best arm identification in multi-armed bandits with delayed feedback , 2018, AISTATS.