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XKDD 2020 : 2nd International Workshop on eXplainable Knowledge Discovery in Data Mining
XKDD 2020 : 2nd International Workshop on eXplainable Knowledge Discovery in Data Mining

XKDD 2020 : 2nd International Workshop on eXplainable Knowledge Discovery in Data Mining

Ghent, Belgium
Event Date: September 14, 2020 - September 14, 2020
Submission Deadline: June 09, 2020
Notification of Acceptance: July 07, 2020
Camera Ready Version Due: July 21, 2020




About

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.


Call for Papers

Topics of interest include, but are not limited to:

  • Explainable Artificial Intelligence
  • Interpretable Machine Learning
  • Transparent Data Mining
  • Explainability in Clustering Analysis
  • Technical Aspects of Algorithms for Explanation
  • Explaining Black Box Decision Systems
  • Adversarial Attack-based Models
  • Counterfactual and Prototype-based Explanations
  • Causal Discovery for Machine Learning Explanation
  • Fairness Checking
  • Fair Machine Learning
  • Explanation for Privacy Risk
  • Ethics Discovery for Explainable AI
  • Privacy-Preserving Explanations
  • Transparent Classification Approaches
  • Anonymity and Information Hiding Problems in Comprehensible Models
  • Case Study Analysis
  • Experiments on Simulated and Real Decision Systems
  • Monitoring and Understanding System Behavior
  • Privacy Risk Assessment
  • Privacy by Design Approaches for Human Data
  • Statistical Aspects, Bias Detection and Causal Inference
  • Explanation, Accountability and Liability from an Ethical and Legal Perspective
  • Benchmarking and measuring explanation
  • Visualization-based explanations
  • Iterative dialogue explanations



Summary

XKDD 2020 : 2nd International Workshop on eXplainable Knowledge Discovery in Data Mining will take place in Ghent, Belgium. It’s a 1 day event starting on Sep 14, 2020 (Monday) and will be winded up on Sep 14, 2020 (Monday).

XKDD 2020 falls under the following areas: MACHINE LEARNING, DATA MINING, PRIVACY, etc. Submissions for this Workshop can be made by Jun 09, 2020. Authors can expect the result of submission by Jul 07, 2020. Upon acceptance, authors should submit the final version of the manuscript on or before Jul 21, 2020 to the official website of the Workshop.

Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines.

Other Details of the XKDD 2020

  • Short Name: XKDD 2020
  • Full Name: 2nd International Workshop on eXplainable Knowledge Discovery in Data Mining
  • Timing: 09:00 AM-06:00 PM (expected)
  • Fees: Check the official website of XKDD 2020
  • Event Type: Workshop
  • Website Link: https://kdd.isti.cnr.it/xkdd2020/
  • Location/Address: Ghent, Belgium


Credits and Sources

[1] XKDD 2020 : 2nd International Workshop on eXplainable Knowledge Discovery in Data Mining


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