Skip to main content Skip to main navigation

Publications

Search narrowed by:

Year: 2020
Remove all filters
Displaying results 61 to 70 of 70.

  1. Robert Peharz; Steven Lang; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Guy Van den Broeck; Kristian Kersting; Zoubin Ghahramani

    Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

    In: Proceedings of the 37th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2020), July 13-18, Pages …

  2. Alejandro Molina; Patrick Schramowski; Kristian Kersting

    Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks

    In: 8th International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2020), April 26-30, Addis …

  3. Amos Treiber; Alejandro Molina; Christian Weinert; Thomas Schneider; Kristian Kersting

    CryptoSPN: Expanding PPML beyond Neural Networks

    In: Benyu Zhang; Raluca Ada Popa; Matei Zaharia; Guofei Gu; Shouling Ji (Hrsg.). PPMLP'20: Proceedings of the 2020 Workshop on Privacy-Preserving …

  4. Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Franziska Herbert; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting

    Making deep neural networks right for the right scientific reasons by interacting with their explanations

    In: Nature Machine Intelligence, Vol. 2, No. 8, Pages 476-486, Springer, 2020.

  5. Johannes Czech; Moritz Willig; Alena Beyer; Kristian Kersting; Johannes Fürnkranz

    Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data

    In: Frontiers in Artificial Intelligence, Vol. 3, Pages 0-10, Frontiers, 2020.

  6. 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 …

  7. 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 …

  8. 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, …

  9. 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.

  10. Nandini Ramanan; Mayukh Das; Kristian Kersting; Sriraam Natarajan

    Discriminative Non-Parametric Learning of Arithmetic Circuits

    In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International …

Year