ETMLP 2020: International Workshop on Explainability for Trustworthy ML Pipelines - Naver Labs Europe
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ETMLP 2020

International Workshop on Explainability for Trustworthy ML Pipelines

Co-located with EDBT 2020 (30 March 2020, Copenhagen, Denmark)

ETMLP 2020

Machine learning (ML) is a driving force for many successful applications in Artificial Intelligence. ML pipelines ensure guarantees on the entirety of the system (i.e., horizontal certification) as well as on each single component (i.e., vertical certification). The horizontal certification covers the full pipeline from data acquisition to data visualization. Moreover, it spans over user-centered, technical, financial, and regulatory aspects of the system. The vertical certification exploits the theory of ML to guarantee error bounds, sampling complexity, energy consumption, execution time, time-to-think, and memory and communication demands. The understandability of an ML pipeline in its entirety requires the collaboration of researchers from the database and the ML communities.

ETMLP workshop will examine the aforementioned opportunities and their associated challenges. The main objective of this workshop is to create a forum where researchers from machine learning, data management, and practitioners engage with ideas around explainability and certified trustworthiness of ML pipelines, at the pipeline level, as well as the component level.

The ultimate goal of the workshop is to discuss recommendations for further work in science and industry and society regarding explainable ML pipelines.

Important dates

Workshop date: 30 March 2020

Submissions: 20 December 2019, 11:59PM CET

Notification of outcome: 24 January 2020, 11:59PM CET (before EDBT 2020 early registration deadline)

Camera ready due: 31 January 2020, 11:59PM CET

The goal of the workshop is to reach a more comprehensive view of the methods and measures for explainability and trustworthiness of machine learning pipelines by bringing together researchers from machine learning, data mining, and databases.
Topics of interest include but are not limited to the followings: challenges of explainable AI, explaining black-box ML models, interpretable machine learning, error and uncertainty bounds, traceability and provenance of ML Pipelines, visual analytics for enabling explanations, robust methods, algorithmic bias, fairness-aware machine learning.

We invite authors to submit either of the following:

  • regular papers: original, unpublished research papers that are not being considered for publication in any other venue;
  • abstract papers: for visionary and work-in-progress ideas.

Regular papers should be maximally 6 pages in length. Abstracts should be maximally one page long. Both page limits exclude references. Abstracts will be only considered for an oral presentation at the workshop and won’t be included in the proceedings of the workshop. Papers must follow the latest ACM Proceedings format (2020). The ETMLP 2020 workshop is single-blind.

Submissions will be handled through EasyChair: https://easychair.org/conferences/?conf=etmlp2020.

Important dates

Workshop date: 30 March 2020

Submissions: 20 December 2019, 11:59PM CET

Notification of outcome: 24 January 2020, 11:59PM CET (before EDBT 2020 early registration deadline)

Camera ready due: 31 January 2020, 11:59PM CET

More information coming soon!

Workshop Chairs

Behrooz Omidvar-Tehrani (NAVER LABS Europe, co-chair)
Katharina Morik (TU Dortmund, co-chair)
Jean-Michel Renders (NAVER LABS Europe, co-chair)

Program Committee

Sihem Amer-Yahia (CNRS, France)
Francesco Bonchi (ISI Foundation, Italy, and Eurecat Barcelona, Spain)
Vassilis Christophides (University of Crete, Greece and Institute for Advanced Studies, Cergy France)
Joao Comba (UFRGS,Brazil)
Yanlei Diao (Ecole Polytechnique, France)
Fosca Giannotti (Information Science and Technology Institute A. Faedo, Italy)
Dimitrios Gunopulos (National and Kapodistrian University of Athens, Greece)
Thomas Liebig (Materna Information and Communications SE, Germany)
Adrian Mos (NAVER LABS Europe, France)
Dino Pedreschi (University of Pisa, Italy)
Nico Piatkowski (TU Dortmund, Germany)
Stefan Rüping (Fraunhofer Institute for Intelligent Analysis and Information Systems, Germany)
Eric Simon (SAP, France)
Divesh Srivastava (AT&T Labs, USA)
Thibaut Thonet (NAVER LABS Europe, France),
Ioannis Tsamardinos (University of Crete, Greece)

More information coming soon!

More information coming soon!

For question or information request, please send us an email to etmlp@naverlabs.com.

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