{"type":"ScholarlyArticle","title":"Auxiliary Information Regularized Machine for Multiple Modality Feature Learning","authors":[{"name":"Yang Yang","slug":"yang-yang","given":"Yang","family":"Yang","affiliation":""},{"name":"Han-Jia Ye","slug":"han-jia-ye","given":"Han-Jia","family":"Ye","affiliation":""},{"name":"De-Chuan Zhan","slug":"de-chuan-zhan","given":"De-Chuan","family":"Zhan","affiliation":""},{"name":"Yuan Jiang","slug":"yuan-jiang","given":"Yuan","family":"Jiang","affiliation":""}],"abstract":"In real world applications, data are often with multiple modalities. Previous works assumed that each modality contains sufficient information for target and can be treated with equal importance. However, it is often that different modalities are of various importance in real tasks, e.g., the facial feature is weak modality and the fingerprint feature is strong modality in ID recognition. In this paper, we point out that different modalities should be treated with different strategies and propose the Auxiliary information Regularized Machine (ARM), which works by extracting the most discriminative feature subspace of weak modality while regularizing the strong modal predictor. Experiments on binary and multi-class datasets demonstrate the advantages of our proposed approach ARM.","doi":null,"url":"https://ijcai.org/proceedings/2015/150","pdf":"https://ijcai.org/proceedings/2015/0150.pdf","markdown":"https://ijcai.org/proceedings/2015/150.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/150","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":"Machine Learning","track":"Main Track","number":150,"pages":{"first":1033,"last":1038},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}