KDML 2018 - Call for Papers

Workshop on Knowledge Discovery, Data Mining and Machine Learning

KDML is a workshop series that aims at bringing together the German Machine Learning and Data Mining community. The KDML 2018 Workshop is co-located with the annual LWDA 2018 – Learning, Knowledge, Data, and Analysis – conference and will take place August 22nd to 24th, 2018, at the University of Mannheim in Germany.

We invite submissions on all aspects of data mining, knowledge discovery, and machine learning. In addition to original research, we also invite reports on preliminary results and resubmissions of recently published articles. Moreover, KDML explicitly invites student submissions.

 

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
  • Multiobjective learning
  • Deep learning
  • Representation and embedding learning
  • Temporal, spatial, and spatiotemporal data mining
  • Unstructured and semi-structured data mining
  • Network, graph, and Web mining
  • Text mining and mining
  • Distributed data mining
  • Data stream mining
  • Visual analytics
  • Big data
  • Probabilistic programming, statistical relational learning, and systems AI
  • Semantics in data mining and machine learning
  • Applications of data mining in all domains including social media digital libraries, bioinformatics, and finance
  • Open source frameworks and tools for data mining and machine learning

 

Types of Submissions

We solicit submissions under three different models:

  • full papers (up to 12 pages, peer-reviewed and to be published by LWDA)
  • short papers (5 page short paper, peer-reviewed); these may included, e.g., visionary ideas, work in progress, demonstration systems, industrial challenges, etc.
  • presentations of papers accepted at major KDML conferences (e.g., ECML, ICML, KDD, NIPS, IJCAI, AAAI, ICDM, etc.); those can be presented and discussed at the KDML workshop, but will not be included in the LWDA proceedings 


For all submission models, authors will have the opportunity to give a presentation at KDML. Depending on the number of submissions, this may include both oral and poster presentations. Accepted full and short papers will be included in the LWDA proceedings.
Submissions are welcome in English and German. However, submissions in English are preferred. All papers have to be formatted according to theSpringer LNCS guidelines and are to be submitted as PDF files to EasyChair using this link. Please select the track Knowledge Discovery, Data Mining and Machine Learning.
At least two independent reviewers will review both full and short paper submissions. The conference proceedings will be published asCEUR Workshop Proceedings and will be indexed by DBLP. All workshop participants have to register for the LWDA 2018 conference.

Important Dates

  • 17.06.2018: Deadline for submissions (extended)
  • 08.07.2018: Notification
  • 22.07.2018: Camera Ready Papers
  • 22.08.-24.08.2018: LWDA 2018 Conference

 

Program Chairs

Prof. Dr. Kristian Kersting, TU Darmstadt

Prof. Dr. Heiko Paulheim, Universität Mannheim



Program Committee

  • Martin Atzmueller, Tilburg University
  • Christian Bauckhage, Fraunhofer
  • Carsten Binnig, TU Darmstadt
  • Bernd Bischl, Ludwig Maximilian University of Munich
  • Ulf Brefeld, Leuphana Universität Lüneburg
  • Markus Döhring, Hochschule Darmstadt
  • Johannes Fürnkranz, TU Darmstadt
  • Joachim Giesen, Friedrich-Schiller Universitaet Jena
  • Goran Glavaš, University of Mannheim
  • Stephan Günnemann, Technical University of Munich
  • Andreas Hotho, University of Wuerzburg
  • Tomas Kliegr, University of Economics, Prague
  • Marius Kloft, TU Kaiserslautern
  • Florian Lemmerich, GESIS - Leibniz Institute for the Social Sciences \& University of Koblenz-Landau
  • Thomas Liebig, TU Dortmund
  • Nico Piatkowski, AI Group, TU Dortmund
  • Petar Ristoski, iBM Research-Almaden
  • Ute Schmid, Faculty Information Systems and Applied Computer Science, University of Bamberg
  • Isabel Valera, MPI for Intelligent Systems
  • Anontio Vergari, Max-Planck-Institute for Intelligent Systems
  • Stefan Wrobel, Fraunhofer IAIS & Univ. of Bonn