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Publications

Displaying results 971 to 980 of 6344.

  1. Nils Boeschen; Tobias Ziegler; Carsten Binnig

    GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP

    In: Proceedings of the ACM on Management of Data (PACMMOD), Vol. 2, No. 6, Pages 237:1-237:26, ACM Digital Library, 2024.

  2. Carsten Binnig; Andreas Henrich; Daniela Nicklas; Maximilian E. Schüle; Klaus Meyer-Wegener (Hrsg.)

    Datenbanksysteme für Business, Technologie und Web (BTW 2025) Workshopband, Bamberg, Germany, March 3-7, 2025

    GI-Fachtagungen (BTW), LNI, Vol. P-363, Gesellschaft für Informatik e.V. 2025.

  3. Carsten Binnig; Eric Sedlar

    21(^mboxst) International Workshop on Data Management on New Hardware (DaMoN)

    In: Volker Markl; Joseph M. Hellerstein; Azza Abouzied (Hrsg.). Companion of the 2025 International Conference on Management of Data, SIGMOD/PODS 2025, Berlin, Germany, June 22-27, 2025. ACM SIGMOD International Conference on Management of Data (SIGMOD), Pages 868-869, ACM, 2025.

  4. Carsten Binnig; Danica Porobic

    Panel on AI for Future Databases: A New Beginning or a Boulevard of Broken Dreams?

    In: Volker Markl; Joseph M. Hellerstein; Azza Abouzied (Hrsg.). Companion of the 2025 International Conference on Management of Data, SIGMOD/PODS 2025, Berlin, Germany, June 22-27, 2025. ACM SIGMOD International Conference on Management of Data (SIGMOD), Pages 1-1, ACM, 2025.

  5. Quentin Delfosse; Patrick Schramowski; Martin Mundt; Alejandro Molina; Kristian Kersting

    Adaptive Rational Activations to Boost Deep Reinforcement Learning

    In: Proceedings of the International Conference on Representation Learning (ICLR). International Conference on Learning Representations (ICLR-2024), OpenReview.net, 2024.

  6. Lukas Struppek; Dominik Hintersdorf; Kristian Kersting

    Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks

    In: International Conference on Learning Representations (ICLR). International Conference on Learning Representations (ICLR-2024), OpenReview, 2024.

  7. Lukas Struppek; Minh Hieu Le; Dominik Hintersdorf; Kristian Kersting

    Exploring the Adversarial Capabilities of Large Language Models

    2024.

  8. Saurabh Mathur; Veerendra P. Gadekar; Rashika Ramola; Peixin Wang; Ramachandran Thiruvengadam; David M. Haas; Shinjini Bhatnagar; Nitya Wadhwa; Garbhini Study Group; Predrag Radivojac; Himanshu Sinha; Kristian Kersting; Sriraam Natarajan

    Modeling Multiple Adverse Pregnancy Outcomes: Learning from Diverse Data Sources

    In: Joseph Finkelstein; Robert Moskovitch; Enea Parimbelli (Hrsg.). Artificial Intelligence in Medicine - 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9-12, 2024, Proceedings, Part I. Conference on Artificial Intelligence in Medicine (AIME), Pages 293-302, Lecture Notes in Computer Science, Vol. 14844, Springer, 2024.

  9. Jonas Seng; Florian Peter Busch; Kristian Kersting

    Causality in Flux: Continual Adaptation of Causal Knowledge via Evidence Matching

    In: Martin Mundt; Keiland W. Cooper; Devendra Singh Dhami; Tyler L. Hayes; Rebecca Herman; Adéle Ribeiro; James Seale Smith (Hrsg.). Proceedings of The Second AAAI Bridge Program on Continual Causality. AAAI Bridge Program on Continual Causality, February 20-21, Vancouver, Canada, Pages 11-20, Proceedings of Machine Learning Research (PMLR), Vol. 268, PMLR, 2024.

  10. Wolfgang Stammer; Felix Friedrich; David Steinmann; Manuel Brack; Hikaru Shindo; Kristian Kersting

    Learning by Self-Explaining

    In: Transactions on Machine Learning Research (TMLR), Vol. 2024, Pages 1-35, arXiv, 2024.

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