Wednesday September 14, 2022 at 10am. (room A711 and online, please ask the link to the organizers)
Tomáš Kroupa (Czech Technical University in Prague)
Title: Coalitional Games for Explainable Machine Learning
Black-box machine learning models rarely have a built-in mechanism to explain and interpret their output. This deficiency has led to a recent interest in explainability methods for ML and AI. From the game-theoretic point of view, it is notable that the most useful interpretation methods are based on the Shapley and Banzhaf values from the coalitional games. In the talk, I will review the existing approaches to defining such games and computing their value. I will also mention the problems arising from the applications of such methods to generative models containing complex interactions among features.