picture
CV

Marek Petrik

I graduated from University of Massachusetts Amherst with my advisor Shlomo Zilberstein.
My main interests are in approximate dynamic programming, machine learning, robust and risk-sensitive optimization, and mathematical optimization.

Contact Information

IBM T.J. Watson Research Center
Yorktown Heights, NY 10598
Cell-phone: +1-413-230-7479
You can still email me at: petrik@cs.umass.edu
ibm

Papers and Talks [bib]

The Price of Dynamic Inconsistency for Distortion Risk Measures
Pu Huang, Dan Iancu, Marek Petrik, Dharmashankar Subramanian. (to be) Submitted, 2011 [PDF]
Distributionally Robust Approach to Approximate Dynamic Programming
Marek Petrik. Submitted, 2011. [PDF]
Linear Dynamic Programs for Resource Management
Marek Petrik and Shlomo Zilberstein. Proceedings of Conference on Artificial Intelligence (AAAI) 2011 [Computational Sustainability Track]. [PDF]
Robust Approximate Bilinear Programming for Value Function Approximation
Marek Petrik and Shlomo Zilberstein. Submitted to Journal of Machine Learning Research 2010/2011. [PDF]
Optimization-based Approximate Dynamic Programming
Marek Petrik. Ph.D. Dissertation [Single Spaced] Double Spaced [Slides]
Feature Selection Using Regularization in Approximate Linear Program for Markov Decision Processes
Marek Petrik, Gavin Taylor, Ron Parr, Shlomo Zilberstein. International Conference on Machine Learning (ICML) 27, 2010. [PDF]
Technical Report (includes proofs and algorithms): arXiv 1005.1860 [PDF]
Robust Value Function Approximation Using Bilinear Programming
Marek Petrik and Shlomo Zilberstein. Advances in Neural Information Processing Systems (NIPS) 22, 2009. [PDF]
Technical Report (includes proofs) UM-CS-2009-052 [PDF]
A Bilinear Programming Approach for Multiagent Planning
Marek Petrik and Shlomo Zilberstein. Journal of Artificial Intelligence Research 35:235-274, 2009. [PDF]
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation
Jeff Johns and Marek Petrik and Sridhar Mahadevan. European Conference on Machine Learning 2009, and Machine Learning. [Link]
Robust Approximate Optimization for Large Scale Planning Problems
Marek Petrik. AAAI Doctoral Consortium 2009. [PDF]
Constraint Relaxation in Approximate Linear Programs
Marek Petrik and Shlomo Zilberstein. International Conference on Machine Learning (ICML) 2009. [PDF]
Blood Management Using Approximate Linear Programming
Marek Petrik and Shlomo Zilberstein. Presented at INFORMS Computing Society Meeting, Charleston, SC 2009. [PDF]
Biasing Approximate Dynamic Programming with a Lower Discount Factor
Marek Petrik and Bruno Scherrer. Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS) 2008/2009. [PDF]
Learning Heuristic Functions Through Approximate Linear Programming
Marek Petrik and Shlomo Zilberstein. International Conference on Automated Planning and Scheduling (ICAPS) 2008. [PDF]
Interaction Structure and Dimensionality Reduction in Decentralized MDPs
Martin Allen and Marek Petrik and Shlomo Zilberstein. In the National Conference on Artificial Intelligence (AAAI), 2008. Short paper. [PDF]
Tech report #UM-CS-2008-11 [PDF]
A Successive Approximation Algorithm for Coordination Problems
Marek Petrik and Shlomo Zilberstein. In the 9th International Symposium on Artificial Intelligence and Mathematics, Fort Lauderdale, Florida, January, 2008 [PDF]
Anytime Coordination Using Separable Bilinear Programs
Marek Petrik, Shlomo Zilberstein. In the National Conference on Artificial Intelligence (AAAI), 2007. (Corrected) [PDF]
An Analysis of Laplacian Methods for Value Function Approximation in MDPs.
Marek Petrik. In the International Joint Conference on Artificial Intelligence (IJCAI), 2007. (Corrected) [PDF]
Average-Reward Decentralized Markov Decision Processes.
Marek Petrik, Shlomo Zilberstein. In the International Joint Conference on Artificial Intelligence (IJCAI), 2007. [PDF]
Learning Parallel Portfolios of Algorithms
Marek Petrik, Shlomo Zilberstein Annals of Mathematics and Artificial Intelligence, 48(1-2):85-106, 2006 (Preliminary) [PDF]
Learning Static Parallel Portfolios of Algorithms.
Marek Petrik, Shlomo Zilberstein. In the 9th International Symposium on Artificial Intelligence and Mathematics, Fort Lauderdale, Florida, January 4-6, 2006. [PDF]
Learning Parallel Portfolios of Algorithms.
Marek Petrik. Diploma (Master) Thesis at Comenius University. Defended on June 7th 2005. [PDF] [Code] [Slides]
Constrained Dynamic Programming for TSPTW.
Marek Petrik. Whitestein Technologies Technical Report. [Email]
Statistically Optimal Combination of Algorithms.
Marek Petrik. In the local proceedings of Sofsem 2005. (Best Student Poster). [PDF]