Learning Optimal Chain Graphs with Answer Set Programming
2015 (English)In: Proceedings of the Thirty-First Conference (2015) Uncertainty In Artificial Intelligence / [ed] Marina Meila and Tom Heskes, AUAI Press , 2015, 822-831 p.Conference paper (Refereed)
Learning an optimal chain graph from data is an important hard computational problem. We present a new approach to solve this problem for various objective functions without making any assumption on the probability distribution at hand. Our approach is based on encoding the learning problem declaratively using the answer set programming (ASP) paradigm. Empirical results show that our approach provides at least as accurate solutions as the best solutions provided by the existing algorithms, and overall provides better accuracy than any single previous algorithm.
Place, publisher, year, edition, pages
AUAI Press , 2015. 822-831 p.
Chain Graphs, Graph Structure Learning, Answer Set Programming
IdentifiersURN: urn:nbn:se:liu:diva-120695ISBN: 978-0-9966431-0-8OAI: oai:DiVA.org:liu-120695DiVA: diva2:847849
Conference on Uncertainty in Artificial Intelligence : July 12‑16, 2015, Amsterdam, Netherlands
FunderSwedish Research Council, 2010-4808