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First name:	Alexander L.
Last name:	Strehl
DBLP:	s/AlexanderLStrehl
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	Conference paper Lihong Li, Michael L. Littman, Thomas J. Walsh, Alexander L. Strehl. Knows what it knows: a framework for self-aware learning.	Machine Learning 2011, Volume 82	(0)	2011
	Book chapter Alexander L. Strehl. Associative Reinforcement Learning.	Encyclopedia of Machine Learning 2010	(0)	2010
	Conference paper Alexander L. Strehl, John Langford, Lihong Li, Sham M. Kakade. Learning from Logged Implicit Exploration Data.	Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, Vancouver, British Columbia, Canada. 2010	(0)	2010
	Journal article Alexander L. Strehl, John Langford, Sham M. Kakade. Learning from Logged Implicit Exploration Data	CoRR 2010, Volume 0	(0)	2010
	Conference paper Alexander L. Strehl, Lihong Li, Michael L. Littman. Reinforcement Learning in Finite MDPs: PAC Analysis.	Journal of Machine Learning Research 2009, Volume 10	(0)	2009
	Journal article Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, Alexander L. Strehl, S. V. N. Vishwanathan. Hash Kernels.	Journal of Machine Learning Research - Proceedings Track 2009, Volume 5	(0)	2009
	Conference paper Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl. Conditional Probability Tree Estimation Analysis and Algorithms.	UAI 2009, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, Montreal, QC, Canada, June 18-21, 2009 2009	(0)	2009
	Conference paper Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl. Conditional Probability Tree Estimation Analysis and Algorithms	CoRR 2009, Volume 0	(0)	2009
	Conference paper Alexander L. Strehl. Probably Approximately Correct (PAC) Exploration in Reinforcement Learning.	International Symposium on Artificial Intelligence and Mathematics (ISAIM 2008), Fort Lauderdale, Florida, USA, January 2-4, 2008 2008	(0)	2008
	Conference paper Peng Dai, Alexander L. Strehl, Judy Goldsmith. Expediting RL by using graphical structures.	7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 3 2008	(0)	2008
	Conference paper John Langford, Alexander L. Strehl, Jennifer Wortman Vaughan. Exploration scavenging.	Machine Learning, Proceedings of the Twenty-Fifth International Conference (ICML 2008), Helsinki, Finland, June 5-9, 2008 2008	(0)	2008
	Conference paper Sharad Goel, John Langford, Alexander L. Strehl. Predictive Indexing for Fast Search.	Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 8-11, 2008 2009	(0)	2008
	Conference paper Alexander L. Strehl, Michael L. Littman. An analysis of model-based Interval Estimation for Markov Decision Processes.	J. Comput. Syst. Sci. 2008, Volume 74	(0)	2008
	Conference paper Alexander L. Strehl, Carlos Diuk, Michael L. Littman. Efficient Structure Learning in Factored-State MDPs.	Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, July 22-26, 2007, Vancouver, British Columbia, Canada 2007	(0)	2007
	Conference paper Alexander L. Strehl, Michael L. Littman. Online Linear Regression and Its Application to Model-Based Reinforcement Learning.	Advances in Neural Information Processing Systems 20, Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 3-6, 2007 2008	(0)	2007
	Conference paper Carlos Diuk, Alexander L. Strehl, Michael L. Littman. A hierarchical approach to efficient reinforcement learning in deterministic domains.	5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, May 8-12, 2006 2006	(0)	2006
	Conference paper Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman. PAC model-free reinforcement learning.	Machine Learning, Proceedings of the Twenty-Third International Conference (ICML 2006), Pittsburgh, Pennsylvania, USA, June 25-29, 2006 2006	(0)	2006
	Conference paper Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh. Experience-efficient learning in associative bandit problems.	Machine Learning, Proceedings of the Twenty-Third International Conference (ICML 2006), Pittsburgh, Pennsylvania, USA, June 25-29, 2006 2006	(0)	2006
	Conference paper Alexander L. Strehl, Lihong Li, Michael L. Littman. Incremental Model-based Learners With Formal Learning-Time Guarantees.	UAI '06, Proceedings of the 22nd Conference in Uncertainty in Artificial Intelligence, Cambridge, MA, USA, July 13-16, 2006 2006	(0)	2006
	Conference paper Alexander L. Strehl, Michael L. Littman. A theoretical analysis of Model-Based Interval Estimation.	Machine Learning, Proceedings of the Twenty-Second International Conference (ICML 2005), Bonn, Germany, August 7-11, 2005 2005	(0)	2005
	Conference paper Bethany R. Leffler, Michael L. Littman, Alexander L. Strehl, Thomas J. Walsh. Efficient Exploration With Latent Structure.	Robotics: Science and Systems I, June 8-11, 2005, Massachusetts Institute of Technology, Cambridge, Massachusetts 2005	(0)	2005
	Conference paper Alexander L. Strehl, Michael L. Littman. An Empirical Evaluation of Interval Estimation for Markov Decision Processes.	16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), 15-17 November 2004, Boca Raton, FL, USA 2004	(0)	2004

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