Call for papers: ECML PKDD International Workshop and Tutorial on eXplainable Knowledge Discovery in Data Mining

Przemyslaw Biecek
ResponsibleML
Published in
2 min readMay 18, 2021

The call for papers for the XKDD Workshop (eXplainable Knowledge Discovery in Data Mining) is open until 23 June. XKDD is a satellite event to the ECML PKDD 2021 conference.

We particularly encourage submissions of papers related to explainability, interpretability and fairness. Previous editions have featured very interesting papers from both theoretical, applied and interdisciplinary perspectives. Accepted papers will be published after the workshop by Springer in a volume of Lecture Notes in Computer Science (LNCS).

There are several reasons why this event is worth attending:

  • Expect an excellent keynote from Prof. Dr. Andreas HOLZINGER (Medical University Graz). Prof. Holzinger is known for his work on Human-Centered AI (HCAI), motivated by efforts to improve human health.
  • Expect a review of the latest results in the area of explainability and fairness during the tutorial session.
  • Expect a series of various interesting presentations along with a place for interesting discussions related to XIML (explainable and interpretable machine learning).

The purpose of XKDD, eXaplaining Knowledge Discovery in Data Mining, is to encourage principled research that will lead to the advancement of explainable, transparent, ethical and fair data mining and machine learning.

Learn more about this workshop at https://kdd.isti.cnr.it/xkdd2021/

Read the full call for papers https://kdd.isti.cnr.it/xkdd2021/xkdd2021cfp.txt

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Przemyslaw Biecek
ResponsibleML

Interested in innovations in predictive modeling. Posts about eXplainable AI, IML, AutoML, AutoEDA and Evidence-Based Machine Learning. Part of r-bloggers.com.