{"type":"ScholarlyArticle","title":"Bounds for Learning from Evolutionary-Related Data in the Realizable Case","authors":[{"name":"Ondrej Kuzelka","slug":"ondrej-kuzelka","given":"Ondrej","family":"Kuzelka","affiliation":""},{"name":"Yuyi Wang","slug":"yuyi-wang","given":"Yuyi","family":"Wang","affiliation":""},{"name":"Jan Ramon","slug":"jan-ramon","given":"Jan","family":"Ramon","affiliation":""}],"abstract":"This paper deals with the generalization ability of classifiers trained from non-iid evolutionary-related data in which all training and testing examples correspond to leaves of a phylogenetic tree. For the realizable case, we prove PAC-type upper and lower bounds based on symmetries and matchings in such trees.","doi":null,"url":"https://ijcai.org/proceedings/2016/237","pdf":"https://ijcai.org/proceedings/2016/0237.pdf","markdown":"https://ijcai.org/proceedings/2016/237.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/237","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":237,"pages":{"first":1655,"last":1660},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}