Schatten p-Norm Based Matrix Regression Model for Image Classification
Nuclear norm minimization problems for finding the minimum rank matrix have been well studied in many areas.Schatten p-norm is an extension of nuclear norm and the rank function.Different p provides flexible choices for suiting for different applications.Differing from the viewpoint of rank,we will use Schatten p-norm to characterize the error matrix between the occluded face image and its ground truth.Thus,a Schatten p-norm based matrix regression model is presented and a general framework for solving Schatten p-norm minimization problem with an added lq regularization is solved by alternating direction method of multipliers (ADMM).The experiments for image classification and face reconstruction show that our algorithm is more effective and efficient,and thus can act as a fast solver for matrix regression problem.
Schatten p-norm ADMM face recognition face reconstruction
Lei Luo Jian Yang Jinhui Chen Yicheng Gao
School of Computer Science and Engineering Nanjing University of Science and Technology,Nanjing 210094,China
国际会议
Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)
长沙
英文
140-150
2014-11-01（万方平台首次上网日期，不代表论文的发表时间）