Profil Janis Keuper


  • Maschinelles Lernen
    • Large Scale Machine Learning
    • Deep Learning
    • Ensemble Methods
  • Mustererkennung
  • Parallelisierung




  • Keuper, J.; Pfreundt, F.-J.:
    Distributed training of deep neural networks: theoretical and practical limits of parallel scalability.
    Proceedings of the Workshop on Machine Learning in High Performance Computing Environments (MLHPC '16), IEEE Press, Piscataway, NJ, USA, 19-26. DOI:, (2016).
  • Keuper, J.; Pfreundt, F.-J.:
    Asynchronous Parallel Stochastic Gradient Descent: A Numeric Core for calable Distributed Machine Learning Algorithms.
    Proceedings of the Workshop on Machine Learning in High-Performance Computing Environments;, isbn 978-1-4503-4006-9, publisher ACM.
  • Keuper, J.:
    Balancing the Communication Load of Asynchronously Parallelized Machine Learning Algorithms.
    Journal CoRR, volume abs/1510.01155, (2015).


Sammlung der Publikationen von Janis Keuper in der Fraunhofer-Publica