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Publications

Displaying results 611 to 620 of 15095.

  1. Lukas Struppek; Dominik Hintersdorf; Antonio De Almeida Correia; Antonia Adler; Kristian Kersting

    Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks

    In: Kamalika Chaudhuri; Stefanie Jegelka; Le Song; Csaba Szepesvári; Gang Niu; Sivan Sabato (Hrsg.). International Conference on Machine Learning. International Conference on Machine Learning (ICML-2022), July 17-23, Baltimore, Maryland, USA, Pages 20522-20545, Proceedings of Machine Learning Research, Vol. 162, PMLR, 2022.

  2. Martin Mundt; Steven Lang; Quentin Delfosse; Kristian Kersting

    CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability

    In: The Tenth International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2022), April 25-29, OpenReview.net, 2022.

  3. Felix Friedrich; Patrick Schramowski; Christopher Tauchmann; Kristian Kersting

    Interactively Providing Explanations for Transformer Language Models

    In: Stefan Schlobach; María Pérez-Ortiz; Myrthe Tielman (Hrsg.). HHAI 2022: Augmenting Human Intellect - Proceedings of the First International Conference on Hybrid Human-Artificial Intelligence. International Conference on Hybrid Human-Artificial Intelligence (HHAI-2022), June 13-17, Amsterdam, Netherlands, Pages 285-287, Frontiers in Artificial Intelligence and Applications, Vol. 354, IOS Press, 2022.

  4. Patrick Schramowski; Christopher Tauchmann; Kristian Kersting

    Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?

    In: FAccT '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT-22), June 21-24, Seoul, Korea, Republic of, Pages 1350-1361, ISBN 978-1-4503-9352-2, ACM, 2022.

  5. Lukas Struppek; Dominik Hintersdorf; Daniel Neider; Kristian Kersting

    Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

    In: FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT-22), June 21-24, Seoul, Korea, Republic of, Pages 58-69, ISBN 978-1-4503-9352-2, ACM, 2022.

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

    Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2001.05371, Pages 0-10, arXiv, 2020.

  7. Fabrizio Ventola; Karl Stelzner; Alejandro Molina; Kristian Kersting

    Residual Sum-Product Networks

    In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International Conference on Probabilistic Graphical Models (PGM-2020), September 23-25, Aalborg, Denmark, Pages 545-556, Proceedings of Machine Learning Research, Vol. 138, PMLR, 2020.

  8. Xiaoting Shao; Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Thomas Liebig; Kristian Kersting

    Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures

    In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International Conference on Probabilistic Graphical Models (PGM-2020), September 23-25, Aalborg, Denmark, Pages 401-412, Proceedings of Machine Learning Research, Vol. 138, PMLR, 2020.

  9. Tjitze Rienstra; Matthias Thimm; Kristian Kersting; Xiaoting Shao

    Independence and D-separation in Abstract Argumentation

    In: Diego Calvanese; Esra Erdem; Michael Thielscher (Hrsg.). Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning. International Conference on Principles of Knowledge Representation and Reasoning (KR-2020), September 12-18, Rhodes, Greece, Pages 713-722, IJCAI Organization, 2020.

  10. Matej Petkovic; Michelangelo Ceci; Kristian Kersting; Saso Dzeroski

    Estimating the Importance of Relational Features by Using Gradient Boosting

    In: Denis Helic; Gerhard Leitner; Martin Stettinger; Alexander Felfernig; Zbigniew W. Ras (Hrsg.). Foundations of Intelligent Systems - 25th International Symposium, ISMIS 2020, Proceedings. International Symposium on Methodologies for Intelligent Systems (ISMIS-2020), September 23-25, Graz, Austria, Pages 362-371, Lecture Notes in Computer Science (LNCS), Vol. 12117, Springer, 2020.

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