Gellert Weisz
Gellert Weisz
DeepMind
Geverifieerd e-mailadres voor google.com
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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
362018
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
312019
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
272020
Leapsandbounds: A method for approximately optimal algorithm configuration
G Weisz, A György, C Szepesvári
arXiv preprint arXiv:1807.00755, 2018
152018
Exploration-enhanced politex
Y Abbasi-Yadkori, N Lazic, C Szepesvari, G Weisz
arXiv preprint arXiv:1908.10479, 2019
122019
CapsAndRuns: An improved method for approximately optimal algorithm configuration
G Weisz, A Gyorgy, C Szepesvári
International Conference on Machine Learning, 6707-6715, 2019
92019
Inter-device data transfer based on barcodes
J Chien, RI Orton, G Weisz, V Varma
US Patent 9,600,701, 2017
22017
Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions
G Weisz, P Amortila, C Szepesvári
arXiv preprint arXiv:2010.01374, 2020
12020
ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool
G Weisz, A György, WI Lin, D Graham, K Leyton-Brown, C Szepesvari, ...
Advances in Neural Information Processing Systems 33, 2020
2020
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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