Invited Talk
in
Workshop: Subset Selection in Machine Learning: From Theory to Applications

Learning Constraints from Examples

Luc De Raedt


Abstract:

While constraints are ubiquitous in artificial intelligence and constraints are also commonly used in machine learning and data mining, the problem of learning constraints from examples has received less attention. I will discuss the problem of constraint learning in general, and present some recent contributions in the learning of various types of constraints and models for combinatorial optimisation. This includes the learning of formulae in Excel, learning SMT formulae, MAX-SAT and Linear Programs.