DISCRIMINATIVE REGULARIZATION:A NEW CLASSIFIER LEARNING METHOD

作     者：薛晖 Xue Hui

作者机构：南京航空航天大学信息科学与技术学院 

出 版 物：《Transactions of Nanjing University of Aeronautics and Astronautics》 (南京航空航天大学学报（英文版）)

年 卷 期：2009年第26卷第1期

页      面：65-74页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by the National Natural Science Foundation of China(60773061) the Natural Science Foundation of Jiangsu Province(BK2008381) 

主　　题：discriminant analysis classification of information pattern recognition 

摘      要：A novel regularization method -- discriminative regularization （DR）is presented. The method provides a general way to incorporate the prior knowledge for the classification. By introducing the prior information into the regularization term, DR is used to minimize the empirical loss between the desired and actual outputs, as well as maximize the inter-class separability and minimize the intra-class compactness in the output space simultane- ously. Furthermore, by embedding equality constraints in the formulation, the solution of DR can solve a set of linear equations. Classification experiments show the superiority of the proposed DR.