Professor Department of Computing Science University of Alberta Edmonton, Alberta Canada T6G 2E8 
Office: 311 Athabasca Hall Email: szepesva AT cs DOT ualberta DOT ca Phone: (780) 4928581 Fax: (780) 4926393 
[en/hu dict] [RLFA RG] [CMPUT 412] [calendar] [math genealogy] 
Who am I?
Faculty at the Department of Computing Science,
one of the 10 PIs
at AICML,
member of RLAI. On leave from SZTAKI.
However, more importantly, I am the head of a fun family.
If I am the head,
Beáta is the neck.
Our kids are
Dávid,
Réka,
Eszter and
Csongor. 
News

Toward the understanding of partialmonitoring games 

A video made by my daughters, Eszter and Reka (then in grade 9 and 10) about the final project of my 2009 CMPUT 412 class. The video was submitted to the IJCAI09 where it won the "community appreciation award". Well done Eszter and Reka! And thanks for my students who made this possible by their excellent work in the class. 
 Prospective grad students who are interested in joining the Statistical Machine Learning degree specialization program, which is a joint program between our department and the MathStat department should look here. Further info here.
 Coorganizing an ICML2010 workshop with Peter Auer and Samuel Kaski. The topic is Reinforcement Learning and Search in Very Large Spaces
 Recently, I have been working on an RL overview paper, which I plan to keep updating for a while and then eventually I will send it to some journal. The target audience is students and researchers interested in algorithms of reinforcement learning. The survey is fairly comprehensive, yet I tried to keep it succinct (50 pages without references, 65 pages with references). Comments, suggestions are welcome.
 Old news: I am teaching CMPUT 412, Undergraduate robotics. I have decided to write up lecture notes for the course, which will be posted to the website. Stay tuned.
 Gradient Descent Methods for Reinforcement Learning , talk at WUSTL (13/11/2009)
 Cryptography and beyond: my "Lunch and Learn" seminar (29/07/2009)
 Responding to an emergency situation, I have spent a few hours by searching on the IEEE website to collect recent references on applications of RL. Here are the results which are now linked to the page on Successes of RL. See also Satinder's similarly titled page here.
 In Fall 2009 I was teaching Online learning.
 Participating in the "Subspace methods for system identification" reading group discussing this book.
 Participating in the "Beyond Lasso" reading group
 Organizing the Online Learning with Limited Feedback
workshop to be held at COLT09,
June 18, Montreal, Canada.
 I enjoyed participating in Max Planck Symposium on Autonomous Systems in TÃ¼bingen.
 I have graduated my first students at UofA!
 The Compressive sensing reading group was functional during 2008 Fall.
 I gave some talks at MLSS'08, Ile de Re:
 I talked at MLSS'08 (Kioloa) on "Reinforcement Learning". Topics covered: MDPs, dynamic programming  the operatortheoretic approach, (approximate) planning algorithms and the curse of dimensionality, efficient online learning, classical and new algorithms (TD and leastsquares algorithms).
 My slides on batch RL presented at the RL Workshop in Barbados. I gave a summary of what is known (theoretically) and listed ca. 10 open questions. If you are interested in any of these problems, drop me an email!