MPhil-PhD transfer presentation
When: Thu, 30 Nov 2017, 12noon
Who: Simon Odense, City, University of London
Title: Compact Rule Extraction from Probabilistic Neural Networks
Abstract: I will discuss new techniques for extracting M-of-N rules from restricted Boltzmann machines. I will begin by discussing rule extraction and its importance for explainable AI before describing a method for extending the extraction of conjunctive confidence rules to the more compact M-of-N rules. Comparative results between extraction algorithms will be presented and several possible experimental applications will be discussed. I will also discuss methods of assigning confidence values to extracted rules in a logical way and how to factor in compactness/interpretability in the extraction process.