Bandit based monte-carlo planning L Kocsis, C Szepesvári Machine Learning: ECML 2006, 282-293, 2006 | 4506 | 2006 |
The grand challenge of computer Go: Monte Carlo tree search and extensions S Gelly, L Kocsis, M Schoenauer, M Sebag, D Silver, C Szepesvári, ... Communications of the ACM 55 (3), 106-113, 2012 | 325 | 2012 |
Improved monte-carlo search L Kocsis, C Szepesvári, J Willemson Univ. Tartu, Estonia, Tech. Rep 1, 2006 | 182 | 2006 |
Discounted ucb L Kocsis, C Szepesvári 2nd PASCAL Challenges Workshop, 2006 | 173 | 2006 |
Transpositions and move groups in Monte Carlo tree search BE Childs, JH Brodeur, L Kocsis Computational Intelligence and Games, 2008. CIG'08. IEEE Symposium On, 389-395, 2008 | 121 | 2008 |
Efficient Multi-Start Strategies for Local Search Algorithms. A György, L Kocsis J. Artif. Intell. Res.(JAIR) 41, 407-444, 2011 | 93 | 2011 |
Exploiting temporal influence in online recommendation R Pálovics, AA Benczúr, L Kocsis, T Kiss, E Frigó Proceedings of the 8th ACM Conference on Recommender systems, 273-280, 2014 | 76 | 2014 |
Continuous Time Associative Bandit Problems. A György, L Kocsis, I Szabó, C Szepesvári IJCAI, 830-835, 2007 | 36 | 2007 |
Universal parameter optimisation in games based on SPSA L Kocsis, C Szepesvári Machine Learning 63 (3), 249-286, 2006 | 26 | 2006 |
RSPSA: enhanced parameter optimization in games L Kocsis, C Szepesvári, MHM Winands Advances in Computer Games, 39-56, 2006 | 19 | 2006 |
Learning time allocation using neural networks L Kocsis, J Uiterwijk, J van den Herik Computers and Games, 170-185, 2001 | 17 | 2001 |
Fully distributed robust singular value decomposition I Hegedus, M Jelasity, L Kocsis, AA Benczúr Peer-to-Peer Computing (P2P), 14-th IEEE International Conference on, 1-9, 2014 | 16 | 2014 |
Move ordering using neural networks L Kocsis, J Uiterwijk, J van den Herik Engineering of Intelligent Systems, 45-50, 2001 | 14 | 2001 |
Reduced-variance payoff estimation in adversarial bandit problems L Kocsis, C Szepesvári Proceedings of the ECML-2005 Workshop on Reinforcement Learning in Non …, 2005 | 12 | 2005 |
Learning in Lines of Action MHM Winands, L Kocsis, JWHM Uiterwijk, HJ van den Herik | 12* | |
BoostingTree: parallel selection of weak learners in boosting, with application to ranking L Kocsis, A György, AN Bán Machine learning 93 (2-3), 293-320, 2013 | 11 | 2013 |
Temporal difference learning and the Neural MoveMap heuristic in the game of Lines of Action MHM Winands, L Kocsis, J Uiterwijk, HJ van den Herik GAME-ON, 99-103, 2002 | 11 | 2002 |
RecSys Challenge 2014: an ensemble of binary classifiers and matrix factorization R Pálovics, F Ayala-Gómez, B Csikota, B Daróczy, L Kocsis, ... Proceedings of the 2014 Recommender Systems Challenge, 13, 2014 | 10 | 2014 |
Efficient multi-start strategies for local search algorithms L Kocsis, A György Machine Learning and Knowledge Discovery in Databases, 705-720, 2009 | 10 | 2009 |
Learning search decisions L Kocsis Universiteit Maastricht, 2003 | 10 | 2003 |