- Reinforcment Learning Theory
- Exploration versus Exploitation
- Value function approximation
- Structured Policies
- Unsupervised Learning
- Predictive representations of dynamical systems
- Learning structure of time series
- Planning and Scheduling Algorithms
- Statistical Learning Theory
- Learning Motor Control
- PhD from the University of California, San Diego 2007
- MS from the Unversity of California, San Diego, 2004
- BAS in Computer Science from the University of Pittsburgh
- Bala Kalyanasundarum and Eric Wiewiora. "Dynamic Spectrum Allocation"
University of Pittsburgh Undergraduate Research Fair. March, 2000.
- Kirk Pruhs and Eric Wiewiora. "Evaluating the Local Ratio Algorithm for Dynamic Storage",
4th Workshop on Algorithm Engineering and Experiments Jan 2002.
- Eric Wiewiora, Garrison Cottrell and Charles Elkan. "Principled Methods for Advising Reinforcement Learning
Agents", Proceedings of the Twentieth International Conference on
machine Learning. August, 2003.
- Eric Wiewiora. "Potential-Based Shaping and
Q-Value Initialization are Equivalent", Journal of
Artificial Intelligence Research, 2003.
- Eric Wiewiora. "Learning Predictive Representations from a History" Proceedings of the Twentysecond International Conference on Mchine Learning. 2005
Alex Strehl, Lihong Li, Eric Wiewiora, John Langford and Micheal Littman.
"PAC Model-free Reinforcement Learning"
Proceedings of the Twenty-third International Conference on Machine
Andrew Rabinovich, Andrea Vedaldi, Carolina Galleguillos, Eric Wiewiora and Serge Belongie. "Objects in Context", Proceedings of the International Conference on Computer Vision. 2007.