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 22 August 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 the Springer 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 as CEUR 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