Alexander L. Strehl

Publication Activity (10 Years)

Years Active: 2004-2014
Publications (10 Years): 0

Top Topics

Conditional Probabilities

Learning Processes

Native Speakers

Top Venues

Publications

Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
Conditional Probability Tree Estimation Analysis and Algorithms. CoRR (2014)
Alexander L. Strehl, Lihong Li, Michael L. Littman
Incremental Model-based Learners With Formal Learning-Time Guarantees. CoRR (2012)
Lihong Li, Michael L. Littman, Thomas J. Walsh, Alexander L. Strehl
Knows what it knows: a framework for self-aware learning. Mach. Learn. 82 (3) (2011)
Alexander L. Strehl, John Langford, Sham M. Kakade
Learning from Logged Implicit Exploration Data CoRR (2010)
Alexander L. Strehl, John Langford, Lihong Li, Sham M. Kakade
Learning from Logged Implicit Exploration Data. NIPS (2010)
Alexander L. Strehl, Lihong Li, Michael L. Littman
Reinforcement Learning in Finite MDPs: PAC Analysis. J. Mach. Learn. Res. 10 (2009)
Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
Conditional Probability Tree Estimation Analysis and Algorithms CoRR (2009)
Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
Conditional Probability Tree Estimation Analysis and Algorithms. UAI (2009)
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, Alexander L. Strehl, Vishy Vishwanathan
Hash Kernels. AISTATS (2009)
Sharad Goel, John Langford, Alexander L. Strehl
Predictive Indexing for Fast Search. NIPS (2008)
Alexander L. Strehl, Michael L. Littman
An analysis of model-based Interval Estimation for Markov Decision Processes. J. Comput. Syst. Sci. 74 (8) (2008)
Peng Dai, Alexander L. Strehl, Judy Goldsmith
Expediting RL by using graphical structures. AAMAS (3) (2008)
Alexander L. Strehl
Probably Approximately Correct (PAC) Exploration in Reinforcement Learning. ISAIM (2008)
John Langford, Alexander L. Strehl, Jennifer Wortman
Exploration scavenging. ICML (2008)
Alexander L. Strehl, Michael L. Littman
Online Linear Regression and Its Application to Model-Based Reinforcement Learning. NIPS (2007)
Alexander L. Strehl, Carlos Diuk, Michael L. Littman
Efficient Structure Learning in Factored-State MDPs. AAAI (2007)
Carlos Diuk, Alexander L. Strehl, Michael L. Littman
A hierarchical approach to efficient reinforcement learning in deterministic domains. AAMAS (2006)
Alexander L. Strehl, Lihong Li, Michael L. Littman
Incremental Model-based Learners With Formal Learning-Time Guarantees. UAI (2006)
Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman
PAC model-free reinforcement learning. ICML (2006)
Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh
Experience-efficient learning in associative bandit problems. ICML (2006)
Alexander L. Strehl, Michael L. Littman
A theoretical analysis of Model-Based Interval Estimation. ICML (2005)
Bethany R. Leffler, Michael L. Littman, Alexander L. Strehl, Thomas J. Walsh
Efficient Exploration With Latent Structure. Robotics: Science and Systems (2005)
Alexander L. Strehl, Michael L. Littman
An Empirical Evaluation of Interval Estimation for Markov Decision Processes. ICTAI (2004)
Alexander L. Strehl
Ternary codes through ternary designs. Australas. J Comb. 30 (2004)