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Jahr: 2019
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Zeige Ergebnisse 11 bis 20 von 35.

  1. 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.

  2. 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.

  3. Kayhan Dursun; Carsten Binnig; Ugur Çetintemel; Garret Swart; Weiwei Gong

    A Morsel-Driven Query Execution Engine for Heterogeneous Multi-Cores

    In: Proceedings of the VLDB Endowment (PVLDB), Vol. 12, No. 12, Pages 2218-2229, Association for Computing Machinery (ACM), 2019.

  4. Lukas Berg; Tobias Ziegler; Carsten Binnig; Uwe Röhm

    ProgressiveDB - Progressive Data Analytics as a Middleware

    In: Proceedings of the VLDB Endowment (PVLDB), Vol. 12, No. 12, Pages 1814-1817, Association for Computing Machinery (ACM), 2019.

  5. Muhammad El-Hindi; Carsten Binnig; Arvind Arasu; Donald Kossmann; Ravi Ramamurthy

    BlockchainDB - A Shared Database on Blockchains

    In: Proceedings of the VLDB Endowment (PVLDB), Vol. 12, No. 11, Pages 1597-1609, Association for Computing Machinery (ACM), 2019.

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

    DBPal: Weak Supervision for Learning a Natural Language Interface to Databases

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1909.06182, Pages 0-10, arXiv, 2019.

  7. 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.

  8. Muhammad El-Hindi; Martin Heyden; Carsten Binnig; Ravi Ramamurthy; Arvind Arasu; Donald Kossmann

    BlockchainDB - Towards a Shared Database on Blockchains

    In: Peter A. Boncz; Stefan Manegold; Anastasia Ailamaki; Amol Deshpande; Tim Kraska (Hrsg.). Proceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019. ACM SIGMOD International Conference on Management of Data (SIGMOD-2019), June 30 - July 5, Amsterdam, Netherlands, Pages 1905-1908, ACM, 2019.

  9. Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Pranav Subramani; Nicola Di Mauro; Pascal Poupart; Kristian Kersting

    SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1901.03704, Pages 0-10, arXiv, 2019.

  10. Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Xiaoting Shao; Kristian Kersting; Zoubin Ghahramani

    Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

    In: Amir Globerson; Ricardo Silva (Hrsg.). Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence. Conference in Uncertainty in Artificial Intelligence (UAI-2019), July 22-25, Tel Aviv, Israel, Pages 334-344, Proceedings of Machine Learning Research, Vol. 115, AUAI Press, 2019.

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