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Multi-class learning from network data is an important but challenging problem with many applications, including malware detection in computer networks, user modeling in social networks, and protein function prediction in biological networks. Despite the extensive research on large multi-class learning, there are still numerous issues that have not been sufficiently addressed, such as efficiency of...
Dictionary learning for sparse representation has drawn considerable attention in recent years. In particular, the K-SVD algorithm is an efficient approach, and various modifications of the K-SVD have been developed for applications such as face recognition. However, the efficient storage of the dictionary has not been studied. Currently, the dictionary is simply normalized and saved as floating-point...
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