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Publications

Displaying results 221 to 230 of 668.

  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. Benjamin Hilprecht; Andreas Schmidt; Moritz Kulessa; Alejandro Molina; Kristian Kersting; Carsten Binnig

    DeepDB: Learn from Data, not from Queries!

    In: Proceedings of the VLDB Endowment (PVLDB), Vol. 13, No. 7, Pages 992-1005, Association for Computing Machinery (ACM), 2020.

  8. Jan-Tilman Seipp; Felix Köhler; David Harbecke; Leonhard Hennig; Phuc Tran Truong

    Text2Tech - Deep Learning-based Text Mining for Technology Monitoring in Automotive Production

    In: 13th Global TechMining Conference 2023 - Conference Proceedings. Global TechMining Conference, November 10, Global TechMining Conference, 2023.

  9. Muhammad El-Hindi; Zheguang Zhao; Carsten Binnig

    Towards Decentralized Parameter Servers for Secure Federated Learning

    In: Alfredo Cuzzocrea; Oleg Gusikhin; Wil M. P. van der Aalst; Slimane Hammoudi (Hrsg.). Proceedings of the 11th International Conference on Data Science, Technology and Applications. International Conference on Data Science, Technology and Applications (DATA-2022), July 11-13, Lisbon, Portugal, Pages 257-269, SCITEPRESS, 2022.

  10. Luis Octavio Arriaga Camargo; Rebecca Adam; Melvin Laux; Lisa Gutzeit; Marco Ragni; Jan Peters; Frank Kirchner

    Bayesian Inverse Physics for Neuro-Symbolic Robot Learning

    In: Leilani Gilpin; Eleonora Giunchiglia; Pascal Hitzler; Emile van Krieken (Hrsg.). Neurosymbolic Artificial Intelligence, Pages 1-19, IOS Press, 2025.

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