{"type":"ScholarlyArticle","title":"Data Compression for Learning MRF Parameters","authors":[{"name":"Khaled S. Refaat","slug":"khaled-s-refaat","given":"Khaled S.","family":"Refaat","affiliation":""},{"name":"Adnan Darwiche","slug":"adnan-darwiche","given":"Adnan","family":"Darwiche","affiliation":""}],"abstract":"We propose a technique for decomposing and compressing the dataset in the parameter learning problem in Markov random fields. Our technique applies to incomplete datasets and exploits variables that are always observed in the given dataset. We show that our technique allows exact computation of the gradient and the likelihood, and can lead to orders-of-magnitude savings in learning time.","doi":null,"url":"https://ijcai.org/proceedings/2015/532","pdf":"https://ijcai.org/proceedings/2015/0532.pdf","markdown":"https://ijcai.org/proceedings/2015/532.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/532","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Special Track on Machine Learning","track":"Special Track on Machine Learning","number":532,"pages":{"first":3784,"last":3789},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}