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Publikationen

Zeige Ergebnisse 921 bis 930 von 15167.

  1. Adrian Lutsch; Christian Franck; Muhammad El-Hindi; Zsolt István; Carsten Binnig

    An Analysis of AWS Nitro Enclaves for Database Workloads

    In: Proceedings of the 21st International Workshop on Data Management on New Hardware, DaMoN 2025, Berlin, Germany, June 22-27, 2025. International Workshop on Data Management on New Hardware (DaMoN), Pages 5:1-5:8, ACM, 2025.

  2. Matthias Jasny; Muhammad El-Hindi; Tobias Ziegler; Carsten Binnig

    A Wake-Up Call for Kernel-Bypass on Modern Hardware

    In: Proceedings of the 21st International Workshop on Data Management on New Hardware, DaMoN 2025, Berlin, Germany, June 22-27, 2025. International Workshop on Data Management on New Hardware (DaMoN), Pages 14:1-14:5, ACM, 2025.

  3. Matthias Jasny; Tobias Ziegler; Jacob Nelson-Slivon; Viktor Leis; Carsten Binnig

    Synchronizing Disaggregated Data Structures with One-Sided RDMA: Pitfalls, Experiments and Design Guidelines

    In: ACM Transactions on Database Systems (TODS), Vol. 50, No. 1, Pages 4:1-4:40, ACM Digital Library, 2025.

  4. Roman Heinrich; Oleksandr Havrylov; Manisha Luthra; Johannes Wehrstein; Carsten Binnig

    Opening The Black-Box: Explaining Learned Cost Models For Databases

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2507.14495, Pages 1-4, arXiv, 2025.

  5. Johannes Wehrstein; Timo Eckmann; Roman Heinrich; Carsten Binnig

    JOB-Complex: A Challenging Benchmark for Traditional & Learned Query Optimization

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2507.07471, Pages 1-8, a, 2025.

  6. Johannes Wehrstein; Timo Eckmann; Roman Heinrich; Carsten Binnig

    JOB-Complex: A Challenging Benchmark for Traditional & Learned Query Optimization

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2507.07471, Pages 1-14, arXiv, 2025.

  7. Khang Nguyen; An T. Le; Tien Pham; Manfred Huber; Jan Peters; Minh Nhat Vu

    FlowMP: Learning Motion Fields for Robot Planning with Conditional Flow Matching

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2503.06135, Pages 1-7, arXiv, 2025.

  8. Théo Vincent; Tim Lukas Faust; Yogesh Tripathi; Jan Peters; Carlo D'Eramo

    Eau De emphQ-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2503.01437, Pages 1-26, arXiv, 2025.

  9. Nico Bohlinger; Jan Peters

    Massively Scaling Explicit Policy-conditioned Value Functions

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.11949, Pages 1-5, arXiv, 2025.

  10. Daniel Palenicek; Florian Vogt; Jan Peters

    Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.07523, Pages 1-23, arXiv, 2025.

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