4th Open Discussion on Machine Learning

Europe/Berlin
Seminar Room 1 (DESY Hamburg)

Seminar Room 1

DESY Hamburg

Andreas Meyer (DESY), Christoph Wissing (DESY), Dirk Kruecker (DESY)
Description
Machine Learning techniques are a hot topic in data science in general. Also in HEP there is a increasing interest in employing such techniques. This meeting is intended to get an overview about the usage of Machine Learning in the DESY CMS groups, identify common approaches and synergies and understand the needs for central support of tools and/or demands for dedicated computing infrastructures.

Vidyo: https://vidyoportal.cern.ch/join/XiUg4TDWmtVC

Access and Modification pw: cdesy
    • 10:00 10:10
      Introduction - Overview resources 10m
      Speaker: Dirk Kruecker (DESY)
      Slides
    • 10:10 10:40
      Parametrized BDTs 30m
      Speaker: David Brunner (DESY)
      Slides
    • 10:40 11:10
      Relevance propagation 30m
      Speaker: Mareike Meyer (DESY)
      Slides
    • 11:10 11:40
      Automation of CMS workflow recovery 30m
      Speaker: Dr Hamed Bakhshiansohi (DESY)
      Slides
    • 11:40 12:10
      Likelihood ratio in many dimensions 30m
      Speaker: Mr Jonas Rübenach (DESY)
      Slides