Ronald Ortner
71 - 79 out of 79Page size: 10
Research output
- Published
Regret Bounds for Learning State Representations in Reinforcement Learning
Ortner, R., Pirotta, M., Lazaric, A., Fruit, R. & Maillard, O.-A., Dec 2019.Research output: Contribution to conference › Poster › Research › peer-review
- Published
Regret Bounds for Reinforcement Learning via Markov Chain Concentration
Ortner, R., 23 Jan 2020, In: The journal of artificial intelligence research. 67.2020, 1, p. 115-128 14 p.Research output: Contribution to journal › Article › Research › peer-review
- Published
Variational Regret Bounds for Reinforcement Learning
Ortner, R., Gajane, P. & Auer, P., 2019, Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, UAI 2019. p. 81-90Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Regret Bounds for Reinforcement Learning via Markov Chain Concentration
Ortner, R., 26 Aug 2021.Research output: Contribution to conference › Poster › Research › peer-review
- Published
Adaptive Algorithms for Meta-Induction
Ortner, R., 7 Oct 2023, In: Journal for general philosophy of science = Zeitschrift für allgemeine Wissenschaftstheorie. 54.2023, 3, p. 433–450 18 p.Research output: Contribution to journal › Article › Research › peer-review
- Published
Understanding the Gaps in Satisficing Bandits
Rouyer, C., Ortner, R. & Auer, P., 2024.Research output: Contribution to conference › Poster › Research › peer-review
- Published
PAC-Bayesian Analysis of Contextual Bandits
Seldin, Y., Auer, P., Laviolette, F., Shawe-Taylor, J. S. & Ortner, R., 2011.Research output: Contribution to conference › Poster › Research › peer-review
- Published
PAC-Bayesian Analysis of Contextual Bandits
Seldin, Y., Auer, P., Laviolette, F., Shawe-Taylor, J. S. & Ortner, R., 2012, Advances in Neural Information Processing Systems 24. MIT Press, p. 1683-1691Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Quantification of Transfer in Reinforcement Learning via Regret Bounds for Learning Agents
Tuynman, A. & Ortner, R., Sept 2022.Research output: Contribution to conference › Poster › Research › peer-review
