Alexander L. Strehl

26 papers A* 5A 4B 1Misc 1Journal 8Unranked 5

Year	Rank	Type	Title / Venue / Authors
2017	—	`ch.`	Associative Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining Alexander L. Strehl
2014	J	`jnl`	Conditional Probability Tree Estimation Analysis and Algorithms. CoRR Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
2012	J	`jnl`	Incremental Model-based Learners With Formal Learning-Time Guarantees. CoRR Alexander L. Strehl, Lihong Li, Michael L. Littman
2011	J	`jnl`	Knows what it knows: a framework for self-aware learning. Mach. Learn. Lihong Li, Michael L. Littman, Thomas J. Walsh, Alexander L. Strehl
2010	—	`ch.`	Associative Reinforcement Learning. Encyclopedia of Machine Learning Alexander L. Strehl
2010	J	`jnl`	Learning from Logged Implicit Exploration Data CoRR Alexander L. Strehl, John Langford, Sham M. Kakade
2010	—	`conf`	Learning from Logged Implicit Exploration Data. NIPS Alexander L. Strehl, John Langford, Lihong Li, Sham M. Kakade
2009	J	`jnl`	Conditional Probability Tree Estimation Analysis and Algorithms CoRR Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
2009	A	`conf`	Conditional Probability Tree Estimation Analysis and Algorithms. UAI Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
2009	A	`conf`	Hash Kernels. AISTATS Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, Alexander L. Strehl, Vishy Vishwanathan
2009	J	`jnl`	Reinforcement Learning in Finite MDPs: PAC Analysis. J. Mach. Learn. Res. Alexander L. Strehl, Lihong Li, Michael L. Littman
2008	J	`jnl`	An analysis of model-based Interval Estimation for Markov Decision Processes. J. Comput. Syst. Sci. Alexander L. Strehl, Michael L. Littman
2008	—	`conf`	Expediting RL by using graphical structures. AAMAS (3) Peng Dai, Alexander L. Strehl, Judy Goldsmith
2008	A*	`conf`	Exploration scavenging. ICML John Langford, Alexander L. Strehl, Jennifer Wortman
2008	—	`conf`	Predictive Indexing for Fast Search. NIPS Sharad Goel, John Langford, Alexander L. Strehl
2008	Misc	`conf`	Probably Approximately Correct (PAC) Exploration in Reinforcement Learning. ISAIM Alexander L. Strehl
2007	A*	`conf`	Efficient Structure Learning in Factored-State MDPs. AAAI Alexander L. Strehl, Carlos Diuk, Michael L. Littman
2007	—	`conf`	Online Linear Regression and Its Application to Model-Based Reinforcement Learning. NIPS Alexander L. Strehl, Michael L. Littman
2006	A	`conf`	A hierarchical approach to efficient reinforcement learning in deterministic domains. AAMAS Carlos Diuk, Alexander L. Strehl, Michael L. Littman
2006	A*	`conf`	Experience-efficient learning in associative bandit problems. ICML Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh
2006	A	`conf`	Incremental Model-based Learners With Formal Learning-Time Guarantees. UAI Alexander L. Strehl, Lihong Li, Michael L. Littman
2006	A*	`conf`	PAC model-free reinforcement learning. ICML Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman
2005	A*	`conf`	A theoretical analysis of Model-Based Interval Estimation. ICML Alexander L. Strehl, Michael L. Littman
2005	—	`conf`	Efficient Exploration With Latent Structure. Robotics: Science and Systems Bethany R. Leffler, Michael L. Littman, Alexander L. Strehl, Thomas J. Walsh
2004	B	`conf`	An Empirical Evaluation of Interval Estimation for Markov Decision Processes. ICTAI Alexander L. Strehl, Michael L. Littman
2004	J	`jnl`	Ternary codes through ternary designs. Australas. J Comb. Alexander L. Strehl