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2020 – today
- 2022
[j8]Erzsébet Frigó, Levente Kocsis
:
Online convex combination of ranking models. User Model. User Adapt. Interact. 32(4): 649-683 (2022)
2010 – 2019
- 2019
- [c17]Erzsébet Frigó, Levente Kocsis:
Online ranking combination. RecSys 2019: 12-19 - [r4]András A. Benczúr, Levente Kocsis, Róbert Pálovics:
Online Machine Learning Algorithms over Data Streams. Encyclopedia of Big Data Technologies 2019 - [r3]András A. Benczúr, Levente Kocsis, Róbert Pálovics:
Online Machine Learning in Big Data Streams: Overview. Encyclopedia of Big Data Technologies 2019 - [r2]András A. Benczúr, Levente Kocsis, Róbert Pálovics:
Recommender Systems Over Data Streams. Encyclopedia of Big Data Technologies 2019 - [r1]András A. Benczúr, Levente Kocsis, Róbert Pálovics:
Reinforcement Learning, Unsupervised Methods, and Concept Drift in Stream Learning. Encyclopedia of Big Data Technologies 2019 - 2018
- [i2]András A. Benczúr, Levente Kocsis, Róbert Pálovics:
Online Machine Learning in Big Data Streams. CoRR abs/1802.05872 (2018) - 2017
- [j7]Róbert Pálovics, Peter Szalai, Júlia Pap, Erzsébet Frigó, Levente Kocsis, András A. Benczúr:
Location-aware online learning for top-k recommendation. Pervasive Mob. Comput. 38: 490-504 (2017) - [c16]Erzsébet Frigó, Róbert Pálovics, Domokos Kelen, Levente Kocsis, András A. Benczúr:
Alpenglow: Open Source Recommender Framework with Time-aware Learning and Evaluation. RecSys Posters 2017 - [c15]Erzsébet Frigó, Róbert Pálovics, Domokos Kelen, Levente Kocsis, András A. Benczúr:
Online Ranking Prediction in Non-stationary Environments. RecTemp@RecSys 2017: 28-34 - 2016
- [j6]István Hegedüs, Árpád Berta, Levente Kocsis, András A. Benczúr, Márk Jelasity:
Robust Decentralized Low-Rank Matrix Decomposition. ACM Trans. Intell. Syst. Technol. 7(4): 62:1-62:24 (2016) - 2015
- [c14]Róbert Pálovics, Peter Szalai, Levente Kocsis, Adrienn Szabó, Erzsébet Frigó, Júlia Pap, Zsófia K. Nyikes, András A. Benczúr:
Solving RecSys Challenge 2015 by Linear Models, Gradient Boosted Trees and Metric Optimization. RecSys Challenge 2015: 4:1-4:4 - [c13]Róbert Pálovics, Peter Szalai, Levente Kocsis, Júlia Pap, Erzsébet Frigó, András A. Benczúr:
Location-Aware Online Learning for Top-k Hashtag Recommendation. LocalRec@RecSys 2015: 36-39 - 2014
- [c12]István Hegedüs, Márk Jelasity, Levente Kocsis, András A. Benczúr:
Fully distributed robust singular value decomposition. P2P 2014: 1-9 - [c11]Róbert Pálovics, András A. Benczúr, Levente Kocsis, Tamás Kiss, Erzsébet Frigó:
Exploiting temporal influence in online recommendation. RecSys 2014: 273-280 - [i1]András György, Levente Kocsis:
Efficient Multi-Start Strategies for Local Search Algorithms. CoRR abs/1401.3894 (2014) - 2013
- [j5]Levente Kocsis, András György, Andrea N. Bán:
BoostingTree: parallel selection of weak learners in boosting, with application to ranking. Mach. Learn. 93(2-3): 293-320 (2013) - 2012
- [j4]Sylvain Gelly, Levente Kocsis, Marc Schoenauer, Michèle Sebag, David Silver, Csaba Szepesvári, Olivier Teytaud:
The grand challenge of computer Go: Monte Carlo tree search and extensions. Commun. ACM 55(3): 106-113 (2012) - 2011
- [j3]András György, Levente Kocsis:
Efficient Multi-Start Strategies for Local Search Algorithms. J. Artif. Intell. Res. 41: 407-444 (2011)
2000 – 2009
- 2009
- [c10]Levente Kocsis, András György:
Efficient Multi-start Strategies for Local Search Algorithms. ECML/PKDD (1) 2009: 705-720 - 2008
- [c9]Benjamin E. Childs, James H. Brodeur, Levente Kocsis:
Transpositions and move groups in Monte Carlo tree search. CIG 2008: 389-395 - 2007
- [c8]András György, Levente Kocsis, Ivett Szabó, Csaba Szepesvári:
Continuous Time Associative Bandit Problems. IJCAI 2007: 830-835 - 2006
- [j2]Levente Kocsis, Csaba Szepesvári:
Universal parameter optimisation in games based on SPSA. Mach. Learn. 63(3): 249-286 (2006) - [c7]Levente Kocsis, Csaba Szepesvári, Mark H. M. Winands:
RSPSA: Enhanced Parameter Optimization in Games. ACG 2006: 39-56 - [c6]Levente Kocsis, Csaba Szepesvári:
Bandit Based Monte-Carlo Planning. ECML 2006: 282-293 - 2003
- [j1]Levente Kocsis, H. Jaap van den Herik, Jos W. H. M. Uiterwijk:
Two Learning Algorithms for Forward Pruning. J. Int. Comput. Games Assoc. 26(3): 165-181 (2003) - 2002
- [c5]Levente Kocsis, Jos W. H. M. Uiterwijk, Eric O. Postma, H. Jaap van den Herik:
The Neural MoveMap Heuristic in Chess. Computers and Games 2002: 154-170 - [c4]Mark H. M. Winands, Levente Kocsis, Jos W. H. M. Uiterwijk, H. Jaap van den Herik:
Learning in Lines of Action. GAME-ON 2002 - 2001
- [c3]Levente Kocsis, Jos W. H. M. Uiterwijk, H. Jaap van den Herik:
Move Ordering Using Neural Networks. IEA/AIE 2001: 45-50 - 2000
- [c2]Levente Kocsis, Jos W. H. M. Uiterwijk, H. Jaap van den Herik:
Learning Time Allocation Using Neural Networks. Computers and Games 2000: 170-185
1990 – 1999
- 1998
- [c1]Levente Kocsis, Nicolae B. Szirbik:
An Unsupervised Training Connectionist Network with Lateral Inhibition. IEA/AIE (Vol. 2) 1998: 603-611
Coauthor Index
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