Inductive Logic Programming (ILP) is a subfield of machine learning, which relies on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining.
The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has expanded its research horizon significantly and welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.
We are pleased to announce that the 27th International Conference on Inductive Logic Programming (ILP 2017) will be held in Orléans from Monday 4th to Wednesday 6th of September 2017.
It will take place in the center of Orléans at Hotel Dupanloup, Centre International Universitaire pour la Recherche, located next to the cathedral.
Thanks to Thanh Binh Nguyen and Duong Khanh Chuong for Orléans pictures.
We are very pleased to announce the 4 Invited Speakers for ILP 2017
Alan Bundy (Professor, University of Edinburgh, United Kingdom)
Marc Boullé (Research Scientist, Orange Labs, France)
Jennifer Neville (Associate Professor, Purdue University, United States)
Matthias Niepert (Senior Researcher, NEC Labs Europe, Germany)
We will have several best paper awards:
A best paper award for regular papers, supported by Springer
A best student award for regular papers and a second best student award for late-breaking papers supported by Machine Learning Journal. In both cases, the first author must be a student at the time paper is submitted.