{"type":"ScholarlyArticle","title":"Supervised Local Tangent Space Alignment for Classification","authors":[{"name":"Hongyu Li","slug":"hongyu-li","given":"Hongyu","family":"Li","affiliation":""},{"name":"Wenbin Chen","slug":"wenbin-chen","given":"Wenbin","family":"Chen","affiliation":""},{"name":"I-Fan Shen","slug":"i-fan-shen","given":"I-Fan","family":"Shen","affiliation":""}],"abstract":"Supervised local tangent space alignment (SLTSA) is an extension of local tangent space alignment (LTSA) to supervised feature extraction. Two algorithmic improvements are made upon LTSA for classification. First a simple technique is proposed to map new data to the embedded low-dimensional space and make LTSA suitable in a changing, dynamic environment. Then SLTSA is introduced to deal with data sets containing multiple classes with class membership information.","doi":null,"url":"https://ijcai.org/proceedings/2005/343","pdf":"https://ijcai.org/proceedings/2005/0343.pdf","markdown":"https://ijcai.org/proceedings/2005/343.md","bibtex":"https://ijcai.org/proceedings/2005/bibtex/343","volume":{"slug":"2005","title":"Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2005","url":"https://ijcai.org/proceedings/2005/","year":2005,"location":"Edinburgh, Scotland, UK","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":343,"pages":{"first":1620,"last":1620},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}