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Gábor Bartók
Gábor Bartók
ETH Zurich
Verified email at ualberta.ca - Homepage
Title
Cited by
Cited by
Year
Incentivizing users for balancing bike sharing systems
A Singla, M Santoni, G Bartók, P Mukerji, M Meenen, A Krause
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
2802015
TF-Agents: A library for reinforcement learning in tensorflow
S Guadarrama, A Korattikara, O Ramirez, P Castro, E Holly, S Fishman, ...
see https://github. com/tensorflow/agents, 2018
1582018
Near-optimally teaching the crowd to classify
A Singla, I Bogunovic, G Bartók, A Karbasi, A Krause
International Conference on Machine Learning, 154-162, 2014
1472014
Partial monitoring—classification, regret bounds, and algorithms
G Bartók, DP Foster, D Pál, A Rakhlin, C Szepesvári
Mathematics of Operations Research 39 (4), 967-997, 2014
1322014
An efficient algorithm for learning with semi-bandit feedback
G Neu, G Bartók
International Conference on Algorithmic Learning Theory, 234-248, 2013
902013
Minimax regret of finite partial-monitoring games in stochastic environments
G Bartók, D Pál, C Szepesvári
Proceedings of the 24th Annual Conference on Learning Theory, 133-154, 2011
572011
Toward a classification of finite partial-monitoring games
A Antos, G Bartók, D Pál, C Szepesvári
Theoretical Computer Science 473, 77-99, 2013
492013
An adaptive algorithm for finite stochastic partial monitoring
G Bartók, N Zolghadr, C Szepesvári
arXiv preprint arXiv:1206.6487, 2012
492012
Partial monitoring with side information
G Bartók, C Szepesvári
International Conference on Algorithmic Learning Theory, 305-319, 2012
372012
Importance weighting without importance weights: An efficient algorithm for combinatorial semi-bandits
G Neu, G Bartók
Journal of Machine Learning Research 17 (154), 1-21, 2016
362016
On actively teaching the crowd to classify
A Singla, I Bogunovic, G Bartok, A Karbasi, A Krause
NIPS Workshop on Data Driven Education, 2013
292013
A near-optimal algorithm for finite partial-monitoring games against adversarial opponents
G Bartók
Conference on Learning Theory, 696-710, 2013
232013
TF-Agents: A library for reinforcement learning in tensorflow (2018)
S Guadarrama, A Korattikara, O Ramirez, P Castro, E Holly, S Fishman, ...
URL https://github. com/tensorflow/agents, 2019
202019
Efficient partial monitoring with prior information
HP Vanchinathan, G Bartók, A Krause
Advances in Neural Information Processing Systems 27, 2014
192014
Fast task-aware architecture inference
E Kokiopoulou, A Hauth, L Sbaiz, A Gesmundo, G Bartok, J Berent
arXiv preprint arXiv:1902.05781, 2019
142019
Gumbel-matrix routing for flexible multi-task learning
K Maziarz, E Kokiopoulou, A Gesmundo, L Sbaiz, G Bartok, J Berent
122019
The role of information in online learning
G Bartók
82012
Task-aware performance prediction for efficient architecture search
E Kokiopoulou, A Hauth, L Sbaiz, A Gesmundo, G Bartók, J Berent
ECAI 2020, 1238-1245, 2020
32020
Flexible multi-task networks by learning parameter allocation
K Maziarz, E Kokiopoulou, A Gesmundo, L Sbaiz, G Bartok, J Berent
arXiv preprint arXiv:1910.04915, 2019
32019
Models of active learning in group-structured state spaces
G Bartók, C Szepesvári, S Zilles
Information and Computation 208 (4), 364-384, 2010
32010
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