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Year: 2019
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Displaying results 21 to 30 of 576.

  1. Martin Pfannemüller; Janick Edinger; Markus Weckesser; Roland Kluge; Manisha Luthra; Robin Klose; Christian Becker; Andy Schürr

    Demo: Visualizing Adaptation Decisions in Pervasive Communication Systems

    In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE International Conference on Pervasive Computing and Communications (PerCom-2019), 22nd International Conference on Pervasive Computing and Communications, Pages 335-337, IEEE, 3/2019.

  2. Martin Pfannemüller; Markus Weckesser; Roland Kluge; Janick Edinger; Manisha Luthra; Robin Klose; Christian Becker; Andy Schürr

    CoalaViz: Supporting Traceability of Adaptation Decisions in Pervasive Communication Systems

    In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE International Conference on Pervasive Computing and Communications (PerCom-2019), 22nd International Conference on Pervasive Computing and Communications, Pages 590-595, IEEE, 3/2019.

  3. Manisha Luthra; Boris Koldehofe; Ralf Steinmetz

    Transitions for Increased Flexibility in Fog Computing: A Case Study on Complex Event Processing

    In: Informatik Spektrum, Vol. 42, No. 4, Pages 244-255, Springer, 2019.

  4. Michael Benedikt; Kristian Kersting; Phokion G. Kolaitis; Daniel Neider

    Logic and Learning (Dagstuhl Seminar 19361)

    In: Dagstuhl Reports, Vol. 9, No. 9, Pages 1-22, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2019.

  5. Patrick Schramowski; Cigdem Turan; Sophie F. Jentzsch; Constantin A. Rothkopf; Kristian Kersting

    BERT has a Moral Compass: Improvements of ethical and moral values of machines

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1912.05238, Pages 0-10, arXiv, 2019.

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

    Random Sum-Product Forests with Residual Links

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1908.03250, Pages 0-10, arXiv, 2019.

  7. Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Pranav Subramani; Nicola Di Mauro; Pascal Poupart; Kristian Kersting

    SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1901.03704, Pages 0-10, arXiv, 2019.

  8. Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Xiaoting Shao; Kristian Kersting; Zoubin Ghahramani

    Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

    In: Amir Globerson; Ricardo Silva (Hrsg.). Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence. Conference in Uncertainty in Artificial Intelligence (UAI-2019), July 22-25, Tel Aviv, Israel, Pages 334-344, Proceedings of Machine Learning Research, Vol. 115, AUAI Press, 2019.

  9. Claas Völcker; Alejandro Molina; Johannes Neumann; Dirk Westermann; Kristian Kersting

    DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets

    In: Peggy Cellier; Kurt Driessens (Hrsg.). Machine Learning and Knowledge Discovery in Databases. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2019), International Workshops of ECML PKDD 2019, Proceedings, Part I, September 16-20, Würzburg, Germany, Pages 28-43, Communications in Computer and Information Science, Vol. 1167, Springer, 2019.

  10. Navdeep Kaur; Gautam Kunapuli; Saket Joshi; Kristian Kersting; Sriraam Natarajan

    Neural Networks for Relational Data

    In: Dimitar Kazakov; Can Erten (Hrsg.). Inductive Logic Programming - 29th International Conference, Proceedings. International Conference on Inductive Logic Programming (ILP-2019), September 3-5, Plovdiv, Bulgaria, Pages 62-71, Lecture Notes in Computer Science (LNAI), Vol. 11770, Springer, 2019.

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