Ronald Ortner
71 - 79 out of 79Page size: 10
Research output
- Published
Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes
Auer, P., Gajane, P. & Ortner, R., 27 Jun 2019.Research output: Contribution to conference › Poster › Research › peer-review
- Published
Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes
Auer, P., Gajane, P. & Ortner, R., 2019, Proceedings of the 32nd Conference on Learning Theory, COLT 2019. p. 138-158Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Adaptively Tracking the Best Arm with an Unknown Number of Distribution Changes
Auer, P., Gajane, P. & Ortner, R., 2018.Research output: Contribution to conference › Paper › peer-review
- Published
Adaptively Tracking the Best Arm with an Unknown Number of Distribution Changes
Auer, P., Gajane, P. & Ortner, R., 2018.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
Adaptive Aggregation for Reinforcement Learning in Average Reward Markov Decision Processes
Ortner, R., 2013, In: Annals of operations research. 208, p. 321-336Research output: Contribution to journal › Article › Research › peer-review
- Published
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information
Auer, P., Chen, Y., Gajane, P., Lee, C.-W., Luo, H., Ortner, R. & Wei, C.-Y., 2019.Research output: Contribution to conference › Abstract › peer-review
- Published
A Boosting Approach to Multiple Instance Learning
Auer, P. & Ortner, R., 2004, Machine Learning, 15th European Conference on Machine Learning, ECML 2004. Springer, p. 63-74Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
A boosting approach to multiple-instance learning
Auer, P. & Ortner, R., 2005Research output: Book/Report › Commissioned report › Transfer › peer-review
