-------- Forwarded Message -------- Subject: [WI] Final CfP: International Workshop on Explainable and Interpretable Machine Learning (XI-ML) Date: Tue, 23 Jun 2020 23:11:15 +0200 From: Martin Atzmüller m.atzmuller@uvt.nl Reply-To: Martin Atzmüller m.atzmuller@uvt.nl To: kdml@cs.uni-kassel.de, fg-db@informatik.uni-rostock.de, wi@aifb.uni-karlsruhe.de
****** Please forward to anyone who might be interested ****** -------------------------------------------------------------- CALL FOR PAPERS International Workshop on Explainable and Interpretable Machine Learning (XI-ML)
to be held on Sept. 21, 2020, Bamberg, Germany co-located with KI 2020
http://www.cslab.cc/xi-ml-2020/ --------------------------------------------------------------
Important Dates: ================ ** Submission Deadline (Extended): Jul 08, 2020 ** Notification of Acceptance: Aug 07, 2020 ** Camera-Ready Versions Due: Aug 21, 2020 ** Workshop date: September 21, 2020
Objectives: =========== With the current scientific discourse on explainable AI (XAI), algorithmic transparency, interpretability, accountability and finally explainability of algorithmic models and decisions, this workshop on explainable and interpretable machine learning tackles these themes from the modeling and learning perspective; it targets interpretable methods and models being able to explain themselves and their output, respectively. The workshop aims to provide an interdisciplinary forum to investigate fundamental issues in explainable and interpretable machine learning as well as to discuss recent advances, trends, and challenges in this area.
Overall, we are interested in receiving papers related to the following topics which include but are not limited to:
* Rule learning for explainable and interpretable machine learning * Assessment of interpretable and explainable models * Cognitive approaches and human concept learning * Human-centered learning and explanation * Causality of machine learning models * Local pattern mining for explanation * Interpretation of black box models * Explanation of black box models * Model-agnostic explanation * Case-based explanation * Evaluation metrics * Empirical research on explainability * Regulations and legal aspects of XAI * Applications of all of the above
Submissions: ============ We will solicit short position papers (2-4 pages) and peer-reviewed research papers (8-16 pages) in LNCS format. Papers should be submitted in EasyChair to https://easychair.org/conferences/?conf=ximl2020
All submitted papers must * be written in English; * contain author names, affiliations, and email addresses; * be formatted according to the Springer LNCS template (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gui...); * be in PDF (make sure that the PDF can be viewed on any platform).
The proceedings will be published in the CEUR Workshop Proceedings series. We will also consider publishing a selection of extended papers in a special issue of an international journal.
Workshop Organizers: ==================== Martin Atzmueller, Tilburg University, The Netherlands Tomáš Kliegr, University of Economics Prague, Czech Republic Ute Schmid, University of Bamberg, Germany
Program Committee: ================== Klaus-Dieter Althoff, University of Hildesheim, Germany Maria Bielikova, Slovak Research Center for AI - slovak.AI Henrik Boström, KTH Royal Institute of Technology, Sweden Amit Dhurandhar, IBM TJ Watson Research Center, USA Johannes Fürnkranz, University of Linz, Austria Martin Holena, Czech Academy of Sciences, Czech Republic Eyke Hüllermeier, University of Paderborn, Germany Kristian Kersting, TU Darmstadt, Germany Grzegorz Nalepa, Jagellonian University, Poland Mykola Pechenizkyi, TU Eindhoven, The Netherlands Marc Plantevit, University Lyon, France Eric Postma, Tilburg University, The Netherlands Celine Rouveirol, Université Sorbonne Paris Nord, France Stefano Teso, KU Leuven, Belgium