{"type":"ScholarlyArticle","title":"Multi-Graph-View Learning for Complicated Object Classification","authors":[{"name":"Jia Wu","slug":"jia-wu","given":"Jia","family":"Wu","affiliation":""},{"name":"Shirui Pan","slug":"shirui-pan","given":"Shirui","family":"Pan","affiliation":""},{"name":"Xingquan Zhu","slug":"xingquan-zhu","given":"Xingquan","family":"Zhu","affiliation":""},{"name":"Zhihua Cai","slug":"zhihua-cai","given":"Zhihua","family":"Cai","affiliation":""},{"name":"Chengqi Zhang","slug":"chengqi-zhang","given":"Chengqi","family":"Zhang","affiliation":""}],"abstract":"In this paper, we propose to represent and classify complicated objects. In order to represent the objects, we propose a multi-graph-view model which uses graphs constructed from multiple graph-views to represent an object. In addition, a bag based multi-graph model is further used to relax labeling by only requiring one label for a bag of graphs, which represent one object. In order to learn classification models, we propose a multi-graph-view bag learning algorithm (MGVBL), which aims to explore subgraph features from multiple graph-views for learning. By enabling a joint regularization across multiple graph-views, and enforcing labeling constraints at the bag and graph levels, MGVBL is able to discover most effective subgraph features across all graph-views for learning. Experiments on real-world learning tasks demonstrate the performance of MGVBL for complicated object classification.","doi":null,"url":"https://ijcai.org/proceedings/2015/555","pdf":"https://ijcai.org/proceedings/2015/0555.pdf","markdown":"https://ijcai.org/proceedings/2015/555.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/555","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":555,"pages":{"first":3953,"last":3958},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}