Chair of Information Technology (150)
Organisational unit: Chair
Research output
- 2019
- 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
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
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
- E-pub ahead of print
Regret Bounds for Learning State Representations in Reinforcement Learning
Ortner, R., Pirotta, M., Lazaric, A., Fruit, R. & Maillard, O-A., 2019, (E-pub ahead of print) Advances in Neural Information Processing Systems. Vol. 32. p. 12717 12727 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- 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
Variational Regret Bounds for Reinforcement Learning
Ortner, R., Gajane, P. & Auer, P., 2019.Research output: Contribution to conference › Paper › peer-review
- 2018
- Published
Online learning with randomized feedback graphs for optimal PUE attacks in cognitive radio networks
Dabaghchian, M., Alipour-Fanid, A., Zeng, K., Wang, Q. & Auer, P., 1 Oct 2018, In: IEEE ACM transactions on networking. 26, 5, p. 2268-2281 14 p., 8466108.Research output: Contribution to journal › Article › Research › peer-review
- Published
A Sliding-Window Approach for Reinforcement Learning in MDPs with Arbitrarily Changing Rewards and Transitions.
Gajane, P., Ortner, R. & Auer, P., 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 › 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
