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Publications

Displaying results 291 to 300 of 667.
  1. Benjamin Hilprecht; Carsten Binnig; Uwe Röhm

    Learning a Partitioning Advisor with Deep Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1904.01279, Pages 0-10, arXiv, 2019.

  2. Benjamin Hilprecht; Carsten Binnig; Uwe Röhm

    Towards learning a partitioning advisor with deep reinforcement learning

    In: Rajesh Bordawekar; Oded Shmueli (Hrsg.). Proceedings of the Second International Workshop on Exploiting Artificial Intelligence Techniques for Data Management. International Workshop on Exploiting Artificial Intelligence Techniques for Data Management (aiDM-2019), aiDM@SIGMOD, July 5, Amsterdam, Netherlands, Pages 6:1-6:4, ACM, 2019.

  3. Abdallah Salama; Alexander Linke; Igor Pessoa Rocha; Carsten Binnig

    XAI: A Middleware for Scalable AI

    In: Slimane Hammoudi; Christoph Quix; Jorge Bernardino (Hrsg.). Proceedings of the 8th International Conference on Data Science, Technology and Applications. International Conference on Data Science, Technology and Applications (DATA-2019), July 26-28, Prague, Czech Republic, Pages 109-120, SciTePress, 2019.

  4. Nathaniel Weir; Prasetya Utama; Alex Galakatos; Andrew Crotty; Amir Ilkhechi; Shekar Ramaswamy; Rohin Bhushan; Nadja Geisler; Benjamin Hättasch; Steffen Eger; Ugur Çetintemel; Carsten Binnig

    DBPal: A Fully Pluggable NL2SQL Training Pipeline

    In: David Maier; Rachel Pottinger; AnHai Doan; Wang-Chiew Tan; Abdussalam Alawini; Hung Q. Ngo (Hrsg.). Proceedings of the 2020 International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD-2020), June 14-19, Pages 2347-2361, ACM, 2020.

  5. Benjamin Hilprecht; Carsten Binnig; Uwe Röhm

    Learning a Partitioning Advisor for Cloud Databases

    In: David Maier; Rachel Pottinger; AnHai Doan; Wang-Chiew Tan; Abdussalam Alawini; Hung Q. Ngo (Hrsg.). Proceedings of the 2020 International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD-2020), June 14-19, Pages 143-157, ACM, 2020.

  6. Benjamin Hilprecht; Carsten Binnig; Tiemo Bang; Muhammad El-Hindi; Benjamin Hättasch; Aditya Khanna; Robin Rehrmann; Uwe Röhm; Andreas Schmidt; Lasse Thostrup; Tobias Ziegler

    DBMS Fitting: Why should we learn what we already know?

    In: 10th Conference on Innovative Data Systems Research. Conference on Innovative Data Systems Research (CIDR-2020), January 12-15, Amsterdam, Netherlands, www.cidrdb.org, 2020.

  7. Noshaba Cheema; Rui Xu; Nam Hee Kim; Perttu Hämäläinen; Vladislav Goliyanik; Marc Habermann; Christian Theobalt; Philipp Slusallek

    Discovering Fatigued Movements for Virtual Character Animation

    In: Conference Papers. ACM SiggraphAsia (SigAsia-2023), December 12-15, Sydney, Australia, ISBN 979-8-4007-0315-7/23/12, ACM, 2023.

  8. Simone Parisi; Simon Ramstedt; Jan Peters

    Goal-driven dimensionality reduction for reinforcement learning

    In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2017), September 24-28, Vancouver, BC, Canada, Pages 4634-4639, IEEE, 2017.

  9. Hany Abdulsamad; Oleg Arenz; Jan Peters; Gerhard Neumann

    State-Regularized Policy Search for Linearized Dynamical Systems

    In: Laura Barbulescu; Jeremy Frank; Mausam; Stephen F. Smith (Hrsg.). Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling. International Conference on Automated Planning and Scheduling (ICAPS-2017), June 18-23, Pittsburgh, Pennsylvania, USA, Pages 419-424, AAAI Press, 2017.

  10. Riad Akrour; Filipe Veiga; Jan Peters; Gerhard Neumann

    Regularizing Reinforcement Learning with State Abstraction

    In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2018), October 1-5, Madrid, Spain, Pages 534-539, IEEE, 2018.