The workshop aims to create links between researchers working on interpretability of machine learning models, in a broad sense. With the objective of animating fruitful discussions and facilitating valuable knowledge sharing, the workshop counts on a pool of re-known speakers in the field.

These are some of the topics that will be addressed during the workshop that may trigger your interest. More information and updates on the program will be available on the event’s website.

• Logic-Based Explainability in Machine Learning
• Consistent Sufficient Explanations and Minimal Local Rules for explaining regression and classification models
• On the Trade-off between Actionable Explanations and the Right to be Forgotten
• Explainability of a Model under stress
• Learning interpretable scoring rules
• Attribution-based Explanations that Provide Recourse Cannot be Robust