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Publications

Displaying results 371 to 380 of 14829.

  1. Kristian Kersting; Tapani Raiko

    'Say EM' for Selecting Probabilistic Models for Logical Sequences

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1207.1353, Pages 0-10, arXiv, 2012.

  2. Martin Schiegg; Marion Neumann; Kristian Kersting

    Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data

    In: Neil D. Lawrence; Mark A. Girolami (Hrsg.). Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics. International Conference on Artificial Intelligence and Statistics (AISTATS-2012), April 21-23, La Palma, Spain, Pages 1002-1011, JMLR Proceedings, Vol. 22, JMLR.org, 2012.

  3. Martin Mladenov; Babak Ahmadi; Kristian Kersting

    Lifted Linear Programming

    In: Neil D. Lawrence; Mark A. Girolami (Hrsg.). Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics. International Conference on Artificial Intelligence and Statistics (AISTATS-2012), April 21-23, La Palma, Spain, Pages 788-797, JMLR Proceedings, Vol. 22, JMLR.org, 2012.

  4. Mirwaes Wahabzada; Kristian Kersting; Christian Bauckhage; Christoph Römer; Agim Ballvora; Francisco Pinto; Uwe Rascher; Jens Leon; Lutz Ploemer

    Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants

    In: Nando de Freitas; Kevin P. Murphy (Hrsg.). Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence. Conference in Uncertainty in Artificial Intelligence (UAI-2012), August 14-18, Catalina Island, CA, USA, Pages 852-862, AUAI Press, 2012.

  5. Christian Thurau; Kristian Kersting; Christian Bauckhage

    Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study

    In: Proceedings of the Twelfth SIAM International Conference on Data Mining. SIAM International Conference on Data Mining (SDM-2012), April 26-28, Anaheim, CA, USA, Pages 684-695, ISBN 978-1-61197-232-0, SIAM / Omnipress, 2012.

  6. Kristian Kersting; Mirwaes Wahabzada; Christoph Römer; Christian Thurau; Agim Ballvora; Uwe Rascher; Jens Leon; Christian Bauckhage; Lutz Plümer

    Simplex Distributions for Embedding Data Matrices over Time

    In: Proceedings of the Twelfth SIAM International Conference on Data Mining. SIAM International Conference on Data Mining (SDM-2012), April 26-28, Anaheim, CA, USA, Pages 295-306, ISBN 978-1-61197-232-0, SIAM / Omnipress, 2012.

  7. Kristian Kersting; Christian Bauckhage; Christian Thurau; Mirwaes Wahabzada

    Matrix Factorization as Search

    In: Peter A. Flach; Tijl De Bie; Nello Cristianini (Hrsg.). Machine Learning and Knowledge Discovery in Databases - European Conference. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2012), September 24-28, Bristol, United Kingdom, Pages 850-853, Lecture Notes in Computer Science, Vol. 7524, Springer, 2012.

  8. Babak Ahmadi; Kristian Kersting; Sriraam Natarajan

    Lifted Online Training of Relational Models with Stochastic Gradient Methods

    In: Peter A. Flach; Tijl De Bie; Nello Cristianini (Hrsg.). Machine Learning and Knowledge Discovery in Databases - European Conference. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2012), September 24-28, Bristol, United Kingdom, Pages 585-600, Lecture Notes in Computer Science, Vol. 7523, Springer, 2012.

  9. Meghdad Mirabi; Leila Fathi; Anton Dignös; Johann Gamper; Carsten Binnig

    A New Primitive for Processing Temporal Joins

    In: Proceedings of the 18th International Symposium on Spatial and Temporal Data, SSTD '23. International Symposium on Spatial and Temporal Data (SSTD-2023), August 23-25, Calgary, AB, Canada, Pages 106-109, ACM, 2023.

  10. Benjamin Hilprecht; Christian Hammacher; Eduardo Souza dos Reis; Mohamed Abdelaal; Carsten Binnig

    DiffML: End-to-end Differentiable ML Pipelines

    In: Proceedings of the Seventh Workshop on Data Management for End-to-End Machine Learning, DEEM 2023. Workshop on Data Management for End-to-End Machine Learning (DEEM-2023), June 18, Seattle, WA, USA, Pages 7:1-7:7, ISBN 979-8-4007-0204-4, ACM, 2023.

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