KDML 2020

Call for Papers

Fachgruppe Knowledge Discovery, Data Mining and Machine Learning

We are accepting late breaking submissions until July 14, 2020.

KDML is a workshop series that aims at bringing together the German Machine Learning and Data Mining community. The KDML 2020 Workshop is co-located with the annual LWDA 2020 – Learning, Knowledge, Data, and Analysis – conference and will take place from September 09, 2020 to September 11, 2020, at the Rheinische Friedrich-Wilhelms-Universität Bonn.

We invite submissions on all aspects of data mining, knowledge discovery, and machine learning. In addition to original research, we also invite resubmissions of recently published articles at major conference venues related to KDML. Moreover, KDML explicitly invites student submissions. Topics of interest cover foundations and applications of all areas of data mining and machine learning. If you would like to submit a paper on a topic and are in doubt about its relevance, please contact the workshop organizers.


Topics of interest include but are not limited to

  • Foundations, models, and theory of machine learning and data mining
  • Supervised, semi-supervised, and unsupervised learning
  • Rule-based learning and pattern mining
  • Multi-objective learning
  • Deep learning
  • Safety related aspects in Deep Learning
  • Explainability in neural networks
  • Representation and embedding learning
  • Time series; spatiotemporal data mining, mining sequences, stream mining
  • Unstructured, semi-structured, multi-modal data mining
  • Network, graph, and Web mining
  • Parallel and Distributed data mining
  • Applications of data mining and machine learning in all domains including healthcare, financial sector, environment, engineering, the Web
  • Open source frameworks and tools for data mining and machine learning


We solicit new contributions (up to 12 pages, peer-reviewed and to be published by LWDA). Shorter contributions (4 pages) are also solicited.

We welcome submissions in English and German, however English is preferred. All papers must be formatted according to the Springer LNCS guidelines. All contributions must be submitted via EasyChair using the link: https://easychair.org/conferences/?conf=lwda2020 ; only PDF is permitted. Please select the track „FG-KDML’“ for your submission.

We further welcome submissions of works accepted recently at top-tier international venues related to KDML (e.g., KDD, ECML, ICML, NIPS, IJCAI, AAAI, ICDM, SDM, etc.). These will not be reviewed but selected by the PC chairs. They will not be included in the LWDA proceedings.


Each submission will be reviewed by at least two independent reviewers.
The conference proceedings will be published as CEUR Workshop Proceedings and will be indexed by DBLP.


All workshop participants have to register for the LWDA 2020 conference.

Papers will be accepted for either long (30 min) or short (10 min) presentations; authors are expected to also prepare a poster presentation of their work.


  • Late breaking submission deadline: July 14, 2020
  • Notification of acceptance: July 24, 2020
  • Camera-ready copy: August 07, 2020
  • LWDA 2020 Conference: September 09 – September 11, 2020


  • Dr. Pascal Welke, Rheinische Friedrich-Wilhelms-Universität Bonn
  • Dr. Nico Piatkowski, Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS


  • Maram Akila, Fraunhofer
  • Klaus-Dieter Althoff, DFKI / University of Hildesheim
  • Martin Atzmueller, Tilburg University
  • Christian Bauckhage, Fraunhofer
  • Rainer Gemulla, University of Mannheim
  • Goran Glavaš, University of Mannheim
  • Stephan Günnemann, Technical University of Munich
  • Marwan Hassani, Eindhoven University of Technology
  • Sibylle Hess, Data Mining Group, TU Eindhoven
  • Andreas Hotho, University of Wuerzburg
  • Sebastian Houben, Fraunhofer
  • Marius Kloft, TU Kaiserslautern
  • Christian Kühnert, Fraunhofer
  • Florian Lemmerich, RWTH Aachen University
  • Thomas Liebig, Materna SE
  • Michael Mock, Fraunhofer
  • Maximilian Poretschkin, Fraunhofer
  • Petar Ristoski, IBM Research-Almaden
  • Ute Schmid, University of Bamberg
  • Erich Schubert, TU Dortmund University
  • Thomas Seidl, Ludwig-Maximilians-University (LMU) Munich
  • Stefan Wrobel, Fraunhofer & University of Bonn