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Subspace learning plays a key role in pattern recognition and machine learning. However, its performance would be degraded when data are corrupted by various occlusions. Low-rank representation (LRR) can recover the corrupted data and explore low-dimensional subspace structures embedded in data. Inspired by low-rank representation and subspace learning, in this paper, we propose a regularized low-rank...
In this paper, we propose a novel feature extraction method called sparse local Fisher discriminant analysis (SLFDA), which is an extension of the local Fisher discriminant analysis (LFDA) algorithm. The proposed method projects the training samples into the range space of local total scatter matrix. Then, it gives the explicit characterization for all solutions of the LFDA. To obtain the sparse projection...
In this paper, we propose a novel feature extraction method called double sparse local Fisher discriminant analysis (DSLFDA), which is an extension of the local Fisher discriminant analysis (LFDA) algorithm. The proposed method combines the idea of sparse representation to construct an adaptive graph to describe the structure information of the samples. Meanwhile, to obtain the sparse projection vectors,...
In recent years, feature extraction method make an achievement in pattern recognition. It extracts not only useful feature for classification, but also reduces the dimension of pattern sample. Linear discriminant analysis is an important method for image recognition, it achieve significant development both in theory and applications. Local fisher discriminant analysis redefines the between-class and...
In recent years, feature extraction methods make an achievement in pattern recognition and computer vision. It extracts not only useful feature for classification, but also reduces the dimension of pattern samples. In this paper, we propose orthogonal supervised spectral discriminant analysis (OSSDA) which motivated by marginal fisher analysis (MFA) and spectral clustering. It put different weights...
The metadata plays an essential role in data warehouse for banks. Based on system developing experience, the paper discusses the categories and functions of metadata, and elaborates how to use metadata to manage system. At last the paper presents the architecture of a Metadata Management System based on data warehouse for banks, and illustrated and analyzed its structure. Application results show...
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