オープン アクセスを義務付けられた論文 - Csaba Szepesvari詳細
一般公開: 78 件
Model-based reinforcement learning with value-targeted regression
A Ayoub, Z Jia, C Szepesvari, M Wang, L Yang
International Conference on Machine Learning, 463-474, 2020
委任: US National Science Foundation, US Department of Defense, Natural Sciences …
On the global convergence rates of softmax policy gradient methods
J Mei, C Xiao, C Szepesvari, D Schuurmans
International conference on machine learning, 6820-6829, 2020
委任: Natural Sciences and Engineering Research Council of Canada
Nearly minimax optimal reinforcement learning for linear mixture markov decision processes
D Zhou, Q Gu, C Szepesvari
Conference on Learning Theory, 4532-4576, 2021
委任: US National Science Foundation, Natural Sciences and Engineering Research …
Online Markov decision processes under bandit feedback
G Neu, A Antos, A György, C Szepesvári
Advances in Neural Information Processing Systems 23, 2010
委任: Hungarian Scientific Research Fund
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
委任: Natural Sciences and Engineering Research Council of Canada
Linear stochastic approximation: How far does constant step-size and iterate averaging go?
C Lakshminarayanan, C Szepesvari
International conference on artificial intelligence and statistics, 1347-1355, 2018
委任: Natural Sciences and Engineering Research Council of Canada
Variational policy gradient method for reinforcement learning with general utilities
J Zhang, A Koppel, AS Bedi, C Szepesvari, M Wang
Advances in Neural Information Processing Systems 33, 4572-4583, 2020
委任: US National Science Foundation, US Department of Defense, Natural Sciences …
The end of optimism? an asymptotic analysis of finite-armed linear bandits
T Lattimore, C Szepesvari
Artificial Intelligence and Statistics, 728-737, 2017
委任: Natural Sciences and Engineering Research Council of Canada
Bandits with delayed, aggregated anonymous feedback
C Pike-Burke, S Agrawal, C Szepesvari, S Grunewalder
International Conference on Machine Learning, 4105-4113, 2018
委任: UK Engineering and Physical Sciences Research Council
Conservative bandits
Y Wu, R Shariff, T Lattimore, C Szepesvári
International Conference on Machine Learning, 1254-1262, 2016
委任: Natural Sciences and Engineering Research Council of Canada
Tighter risk certificates for neural networks
M Pérez-Ortiz, O Rivasplata, J Shawe-Taylor, C Szepesvári
Journal of Machine Learning Research 22 (227), 1-40, 2021
委任: US Department of Defense, Natural Sciences and Engineering Research Council …
Regularized policy iteration with nonparametric function spaces
A Farahm, M Ghavamzadeh, C Szepesvári, S Mannor
Journal of Machine Learning Research 17 (139), 1-66, 2016
委任: Natural Sciences and Engineering Research Council of Canada
Model selection in contextual stochastic bandit problems
A Pacchiano, M Phan, Y Abbasi Yadkori, A Rao, J Zimmert, T Lattimore, ...
Advances in Neural Information Processing Systems 33, 10328-10337, 2020
委任: Natural Sciences and Engineering Research Council of Canada
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
委任: Natural Sciences and Engineering Research Council of Canada
Cumulative prospect theory meets reinforcement learning: Prediction and control
LA Prashanth, C Jie, M Fu, S Marcus, C Szepesvári
International Conference on Machine Learning, 1406-1415, 2016
委任: US National Science Foundation, Natural Sciences and Engineering Research …
The adversarial stochastic shortest path problem with unknown transition probabilities
G Neu, A Gyorgy, C Szepesvári
Artificial Intelligence and Statistics, 805-813, 2012
委任: Hungarian Scientific Research Fund
Coindice: Off-policy confidence interval estimation
B Dai, O Nachum, Y Chow, L Li, C Szepesvári, D Schuurmans
Advances in neural information processing systems 33, 9398-9411, 2020
委任: Natural Sciences and Engineering Research Council of Canada
DCM bandits: Learning to rank with multiple clicks
S Katariya, B Kveton, C Szepesvari, Z Wen
International Conference on Machine Learning, 1215-1224, 2016
委任: Natural Sciences and Engineering Research Council of Canada
PAC-Bayes analysis beyond the usual bounds
O Rivasplata, I Kuzborskij, C Szepesvári, J Shawe-Taylor
Advances in Neural Information Processing Systems 33, 16833-16845, 2020
委任: US Department of Defense, Natural Sciences and Engineering Research Council …
Active learning in heteroscedastic noise
A Antos, V Grover, C Szepesvári
Theoretical Computer Science 411 (29-30), 2712-2728, 2010
委任: Hungarian Scientific Research Fund
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