Sparse multi-task reinforcement learning
暂无分享,去创建一个
Daniele Calandriello | Alessandro Lazaric | Marcello Restelli | A. Lazaric | Marcello Restelli | Daniele Calandriello
[1] John N. Tsitsiklis,et al. Neuro-Dynamic Programming , 1996, Encyclopedia of Machine Learning.
[2] Richard S. Sutton,et al. Introduction to Reinforcement Learning , 1998 .
[3] Masayuki Yamamura,et al. Multitask reinforcement learning on the distribution of MDPs , 2003, Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694).
[4] Eric R. Ziegel,et al. The Elements of Statistical Learning , 2003, Technometrics.
[5] Pierre Geurts,et al. Tree-Based Batch Mode Reinforcement Learning , 2005, J. Mach. Learn. Res..
[6] Charles A. Micchelli,et al. Learning Convex Combinations of Continuously Parameterized Basic Kernels , 2005, COLT.
[7] Massimiliano Pontil,et al. Convex multi-task feature learning , 2008, Machine Learning.
[8] Alan Fern,et al. Multi-task reinforcement learning: a hierarchical Bayesian approach , 2007, ICML '07.
[9] Csaba Szepesvári,et al. Finite-Time Bounds for Fitted Value Iteration , 2008, J. Mach. Learn. Res..
[10] Jean-Philippe Vert,et al. Group lasso with overlap and graph lasso , 2009, ICML '09.
[11] S. Geer,et al. On the conditions used to prove oracle results for the Lasso , 2009, 0910.0722.
[12] Peter Stone,et al. Transfer Learning for Reinforcement Learning Domains: A Survey , 2009, J. Mach. Learn. Res..
[13] Andrew Y. Ng,et al. Regularization and feature selection in least-squares temporal difference learning , 2009, ICML '09.
[14] P. Bickel,et al. SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG SELECTOR , 2008, 0801.1095.
[15] Hui Li,et al. Multi-task Reinforcement Learning in Partially Observable Stochastic Environments , 2009, J. Mach. Learn. Res..
[16] Alessandro Lazaric,et al. Bayesian Multi-Task Reinforcement Learning , 2010, ICML.
[17] Masashi Sugiyama,et al. Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information , 2010, ECML/PKDD.
[18] Jeff G. Schneider,et al. Learning Multiple Tasks with a Sparse Matrix-Normal Penalty , 2010, NIPS.
[19] Martin J. Wainwright,et al. Estimation of (near) low-rank matrices with noise and high-dimensional scaling , 2009, ICML.
[20] Charles A. Micchelli,et al. A Family of Penalty Functions for Structured Sparsity , 2010, NIPS.
[21] Csaba Szepesvári,et al. Error Propagation for Approximate Policy and Value Iteration , 2010, NIPS.
[22] S. Geer,et al. Oracle Inequalities and Optimal Inference under Group Sparsity , 2010, 1007.1771.
[23] Matthew W. Hoffman,et al. Finite-Sample Analysis of Lasso-TD , 2011, ICML.
[24] Matthew W. Hoffman,et al. Regularized Least Squares Temporal Difference Learning with Nested ℓ2 and ℓ1 Penalization , 2011, EWRL.
[25] Andrea Castelletti,et al. Tree-based variable selection for dimensionality reduction of large-scale control systems , 2011, 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).
[26] Sara van de Geer,et al. Statistics for High-Dimensional Data , 2011 .
[27] Shimon Whiteson,et al. Multi-Task Reinforcement Learning: Shaping and Feature Selection , 2011, EWRL.
[28] Eduardo F. Morales,et al. An Introduction to Reinforcement Learning , 2011 .
[29] Alessandro Lazaric,et al. Transfer from Multiple MDPs , 2011, NIPS.
[30] Sara van de Geer,et al. Statistics for High-Dimensional Data: Methods, Theory and Applications , 2011 .
[31] Matthieu Geist,et al. Approximate Modified Policy Iteration , 2012, ICML.
[32] Alessandro Lazaric,et al. Transfer in Reinforcement Learning: A Framework and a Survey , 2012, Reinforcement Learning.
[33] Ronald Parr,et al. Greedy Algorithms for Sparse Reinforcement Learning , 2012, ICML.
[34] Guy Lever,et al. Modelling transition dynamics in MDPs with RKHS embeddings , 2012, ICML.
[35] 松井 秀俊. Statistics for High-Dimensional Data: Methods, Theory and Applications, Peter Buhlman and Sara van de Geer著, Springer, 2011年6月, 558pp., 価格 114,99〓, ISBN 978-3642201912 , 2014 .