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Recently, sparse representation (SR) over a redundant dictionary has become a popular way of representing the data. It has been verified as an efficient and useful tool to promote the discrimination between signals. This work develops a joint learning approach to find the low dimensional discriminative features for high dimensional data. To avoid the high computational cost of direct sparse coding...
Recently, hash algorithms catch amounts of sights in the field of machine learning. Most existing hash methods directly utilize a vector, which can be piped by the column of image matrix, as a unit and adopt some feature extraction functions to project the original data into generally shorter fixed-length values or characters. Then each of these projected real values is quantized or hashed into zero-one...
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