Research output

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  1. Published

    A boosting approach to multiple-instance learning

    Auer, P. & Ortner, R., 2005

    Research output: Book/Report › Commissioned report › Transfer › peer-review

  2. 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. 63-74

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  3. 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

  4. Published

    Adaptive Aggregation for Reinforcement Learning in Average Reward Markov Decision Processes

    Ortner, R., 2013, In: Annals of operations research. 208, p. 321-336

    Research output: Contribution to journal › Article › Research › peer-review

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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. 138-158

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  10. Published

    Algorithmic Learning Theory: 27th International Conference, ALT 2016, Proceedings

    Ortner, R. (Co-editor), Ulrich Simon, H. (Co-editor) & Zilles, S., 2016, Springer.

    Research output: Book/Report › Anthology › Research

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