Csaba Szepesvari
Affiliations: | Computing Science | University of Alberta, Edmonton, Alberta, Canada |
Area:
Computer ScienceGoogle:
"Csaba Szepesvari"Children
Sign in to add trainee| Amir-massoud Farahmand | grad student | 2011 | University of Alberta |
| Yasin Abbasi-Yadkori | grad student | 2012 | University of Alberta |
| Gabor Bartok | grad student | 2012 | University of Alberta |
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Publications
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| Joulani P, György A, Szepesvári C. (2020) A modular analysis of adaptive (non-)convex optimization: Optimism, composite objectives, variance reduction, and variational bounds Theoretical Computer Science. 808: 108-138 |
| Jie C, Prashanth LA, Fu M, et al. (2018) Stochastic Optimization in a Cumulative Prospect Theory Framework Ieee Transactions On Automatic Control. 63: 2867-2882 |
| Lakshminarayanan C, Bhatnagar S, Szepesvari C. (2018) A Linearly Relaxed Approximate Linear Program for Markov Decision Processes Ieee Transactions On Automatic Control. 63: 1185-1191 |
| Kveton B, Szepesvari C, Wen Z, et al. (2015) Cascading bandits: Learning to rank in the cascade model 32nd International Conference On Machine Learning, Icml 2015. 1: 767-776 |
| Bartók G, Foster DP, Pál D, et al. (2014) Partial monitoring - Classification, regret bounds, and algorithms Mathematics of Operations Research. 39: 967-997 |
| Le T, Szepesvari C, Zheng R. (2014) Sequential learning for multi-channel wireless network monitoring with channel switching costs Ieee Transactions On Signal Processing. 62: 5919-5929 |
| Neu G, Gyorgy A, Szepesvari C, et al. (2014) Online Markov decision processes under bandit feedback Ieee Transactions On Automatic Control. 59: 676-691 |
| Antos A, Bartók G, Pál D, et al. (2013) Toward a classification of finite partial-monitoring games Theoretical Computer Science. 473: 77-99 |
| Afkanpour A, Szepesvári C, Bowling M. (2013) Alignment based kernel learning with a continuous set of base kernels Machine Learning. 91: 305-324 |
| Joulani P, György A, Szepesvari C. (2013) Online learning under delayed feedback 30th International Conference On Machine Learning, Icml 2013. 2503-2511 |