Mining patterns in tabular data - A Symbolic AI approach
This session will cover Symbolic AI, which is a vast research field operating human-readable knowledge representations. In particular, we will focus on Pattern Structures formalism that provides a unified language to efficiently mine patterns in tables containing numbers, categories, ngrams, graphs, and other types of data. Such patterns can then be used for mining explainable-by-design implications, clusterings, and multiclass classifiers. The hand-on-section will explore a novel Paspailleur Python package (developed in Loria, set to release in May 2025) that can solve all aforementioned tasks for all aforementioned data.
- Date: June 17, 2025
- Time: Theory: 14:00 - 14:50 / Coffee 14:50 - 15:10 / Lab 15:10 - 16:00
- Location: Nancy-Salle A008 Jean Legras
- Instructor: Egor Dudyrev, Ph.D. Candidate