Gellert Weisz
Gellert Weisz
DeepMind
Verified email at google.com
Title
Cited by
Cited by
Year
Learning with good feature representations in bandits and in rl with a generative model
T Lattimore, C Szepesvari, G Weisz
International Conference on Machine Learning, 5662-5670, 2020
502020
Politex: Regret bounds for policy iteration using expert prediction
Y Abbasi-Yadkori, P Bartlett, K Bhatia, N Lazic, C Szepesvari, G Weisz
International Conference on Machine Learning, 3692-3702, 2019
502019
Sample efficient deep reinforcement learning for dialogue systems with large action spaces
G Weisz, P Budzianowski, PH Su, M Gašić
IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (11 …, 2018
502018
Stacked convolutional auto-encoders for hierarchical feature extraction
O Chen, D Simig, G Weisz
ICANN 2011: Artificial Neural Networks and Machine Learning-ICANN, 52-59, 2011
302011
Leapsandbounds: A method for approximately optimal algorithm configuration
G Weisz, A Gyorgy, C Szepesvári
International Conference on Machine Learning, 5257-5265, 2018
232018
Exploration-enhanced politex
Y Abbasi-Yadkori, N Lazic, C Szepesvari, G Weisz
arXiv preprint arXiv:1908.10479, 2019
162019
Exponential lower bounds for planning in mdps with linearly-realizable optimal action-value functions
G Weisz, P Amortila, C Szepesvári
Algorithmic Learning Theory, 1237-1264, 2021
132021
CapsAndRuns: An improved method for approximately optimal algorithm configuration
G Weisz, A Gyorgy, C Szepesvári
International Conference on Machine Learning, 6707-6715, 2019
122019
Inter-device data transfer based on barcodes
J Chien, RI Orton, G Weisz, V Varma
US Patent 9,600,701, 2017
52017
On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function
G Weisz, P Amortila, B Janzer, Y Abbasi-Yadkori, N Jiang, C Szepesvári
arXiv preprint arXiv:2102.02049, 2021
12021
ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool.
G Weisz, A György, WI Lin, DR Graham, K Leyton-Brown, C Szepesvari, ...
NeurIPS, 2020
2020
Language Understanding and Computational Semantics Cross-Language Neural Dialog State Tracker for Large Ontologies Using Hierarchical Attention.................................
H Sundar, TV Sreenivas, CS Seelamantula, S Lin, MB Cöteli, O Olgun, ...
P: Regret Bounds for Policy Iteration Using Expert Prediction
Y Abbasi-Yadkori, PL Bartle, K Bhatia, N Lazić, C Szepesvári, G Weisz
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Articles 1–13