ECML PKDD International Workshop on

eXplainable Knowledge Discovery in Data Mining

Ghent, Belgium, Monday 14th September 2020

COVID-19 Plan

In line with the organization of ECML-PKDD 2020, the organizers of XKDD 2020 have decided to take the workshop fully virtual. The events of the past few months and the continued safety concerns have led us to make this difficult decision. Our focus now is on creating a virtual conference with the vibrancy, excellence and sense of community that ECML-PKDD has become known for. Thus, all accepted contributions will be published, presented, etc, as normal (although presentations might take a different form). In the coming weeks, the agenda and more programmatic details will be announced, watch the website and our social media posts.

Attending the workshop

The XKDD workshop will be held online as a Zoom Webinar. You can join at the following link:

To participate to the workshop (and the ECML/PKDD 2020 Conference) it is possible to use the Whova Conference app.

Through the ECML/PKDD 2020 Whova APP you will have access to the pre-recorded presentation, read the papers, post your questions, receive upadtes and sicuss with the other attendees.

Browser/desktop version

Mobile version

Get our official event app
For Blackberry or Windows Phone, Click here
For feature details, visit Whova

Call for Papers

In the past decade, machine learning based decision systems have been widely used in a plethora of applications ranging from credit score, insurance risk, and health monitoring, in which accuracy is of the utmost importance. Although the application of these systems may bring myriad benefits, their use might involve some ethical and legal risks, such as codifying biases; jeopardizing transparency and privacy, reducing accountability. Unfortunately, these risks increase and are made more serious by the opacity of these systems, which often are complex and their internal logic is usually inaccessible to humans.

Nowadays most of the Artificial Intelligence (AI) systems are based on machine learning algorithms. The relevance and need of ethics in AI is supported and highlighted by the various initiatives that in the world provide recommendations and guidelines in the direction of making AI-based decision systems explainable and compliant with legal and ethical issues. These include the EU's GDPR regulation which introduces, to some extent, a right for all individuals to obtain ``meaningful explanations of the logic involved'' when automated decision making takes place, the ``ACM Statement on Algorithmic Transparency and Accountability'', the Informatics Europe's ``European Recommendations on Machine-Learned Automated Decision Making'' and ``The ethics guidelines for trustworthy AI'' provided by the EU High-Level Expert Group on AI.

The challenge to design and develop trustworthy AI-based decision systems is still open and requires a joint effort across technical, legal, sociological and ethical domains.

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. The workshop will seek top-quality submissions addressing uncovered important issues related to ethical, explainable and transparent data mining and machine learning. Papers should present research results in any of the topics of interest for the workshop as well as application experiences, tools and promising preliminary ideas. XKDD asks for contributions from researchers, academia and industries, working on topics addressing these challenges primarily from a technical point of view, but also from a legal, ethical or sociological perspective. In the past decade, we have witnessed the increasing deployment of powerful automated decision-making systems in settings ranging from control of safety-critical systems to face detection on mobile phone cameras. Albeit remarkably powerful in solving complex tasks, these systems are typically completely obscure, i.e., they do not provide any mechanism to understand and explore their behavior and the reasons underlying the decisions taken.

Topics of interest include, but are not limited to:

Submissions with an interdisciplinary orientation are particularly welcome, e.g. works at the boundary between ML, AI, infovis, man-machine interfaces, psychology, etc. Research driven by application cases where interpretability matters are also of our interest, e.g., medical applications, decision systems in law and administrations, industry 4.0, etc.

The call for paper can be dowloaded here.

Submission

Electronic submissions will be handled via Easychair.

Papers must be written in English and formatted according to the Springer Lecture Notes in Computer Science (LNCS) guidelines following the style of the main conference (format).

The maximum length of either research or position papers is 16 pages in this format. Overlength papers will be rejected without review (papers with smaller page margins and font sizes than specified in the author instructions and set in the style files will also be treated as overlength).

Authors who submit their work to XKDD 2020 commit themselves to present their paper at the workshop in case of acceptance. XKDD 2020 considers the author list submitted with the paper as final. No additions or deletions to this list may be made after paper submission, either during the review period, or in case of acceptance, at the final camera ready stage.

Condition for inclusion in the post-proceedings is that at least one of the co-authors has presented the paper at the workshop (either digitally or in presence depending on how the situation evolves). Pre-proceedings will be available online before the workshop. A special issue of a relevant international journal with extended versions of selected papers is under consideration.

All accepted papers will be published as post-proceedings in LNCSI and included in the series name Lecture Notes in Computer Science.

All papers for XKDD 2020 must be submitted by using the on-line submission system at Easychair.

Important Dates

  • Paper Submission deadline: June 9th June 19, 2020
  • Accept/Reject Notification: July 7th July 14, 2020
  • Camera-ready deadline: July 21th, 2020
  • Workshop: September 14th, 2020

Organization

Program Committee

Program

Keynote talk
Interpretable Machine Learning - State of the Art and Challenges

Christoph Molnar (LMU Munich)

SlideLive

Efficient estimation of General Additive Neural Networks: a Case Study for CTG data

Paulo Lisboa, Sandra Ortega, Manoj Jayabala, Ivan Oliler (Liverpool John Moores University)

SlideLive

What Would You Ask the Machine Learning Model? Identification of User Needs for Model Explanations Based on Human-Model Conversations.

Michał Kuźba, Przemysław Biecek (University of Warsaw, Warsaw University of Technology)

SlideLive

Analyzing Forward Robustness of Feedforward Deep Neural Networks with LeakyReLU Activation Function through Symbolic Propagation

Giulio Masetti, Felicits Di Giandomenico (ISTI-CNR Pisa)

SlideLive

Break 20 minutes

Keynote talk
Randomization for Fairness

Franesco Bonchi (ISI Foundation)

SlideLive

LimeOut: An Ensemble Approach To Improve Process Fairness

Vaishnavi Bhargava, Miguel Couceiro and Amedeo Napoli (University of Lorraine, CNRS, Inria, LORIA)

SlideLive

Interpretable privacy with optimizable utility

Jan Ramon, Moitree Basu (INRIA - France)

SlideLive

Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks

Francesca Naretto (Scuola Normale Superiore), Roberto Pellungrini (University of Pisa), Fosca Giannotti (ISTI-CNR Pisa)

SlideLive

Approximate Explanations for Classification of Histopathology Patches

Iam Palatnik de Sousa, Marley M B R Vellasco and Eduardo Costa da Silva (Pontifícia Universidade Católica do Rio de Janeiro)

SlideLive

Feedback from workshop participants and conclusion

Venue

The XKDD workshop will be held online as a Zoom Webinar. You can join at the following link:

To participate to the workshop (and the ECML/PKDD 2020 Conference) it is possible to use the Whova Conference app.

Through the ECML/PKDD 2020 Whova APP you will have access to the pre-recorded presentation, read the papers, post your questions, receive upadtes and sicuss with the other attendees.

Browser/desktop version

Mobile version

Get our official event app
For Blackberry or Windows Phone, Click here
For feature details, visit Whova

Partners

This workshop is partially supported by the European Community H2020 Program under research and innovation programme, grant agreement 788352 Pro-Res.

This workshop is partially supported by the European Community H2020 Program under the funding scheme FET Flagship Project Proposal, HumanE-AI.

This workshop is partially supported by the European Community H2020 Program under the funding scheme INFRAIA-2019-1: Research Infrastructures, grant agreement 871042 SoBigData++.

This workshop is partially supported by the European Community H2020 Program under research and innovation programme, grant agreement 825619 AI4EU.

Contacts

All inquires should be sent to

xkdd2020@easychair.org