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Hashing is a popular approximate nearest neighbor search approach for large-scale image retrieval. Supervised hashing, which incorporates similar-ity/dissimilarity information on entity pairs to improve the quality of hashing function learning, has recently received increasing attention. However, in the existing supervised hashing methods for images, an(More)
Multi-view clustering, which seeks a partition of the data in multiple views that often provide complementary information to each other, has received considerable attention in recent years. In real life clustering problems, the data in each view may have considerable noise. However, existing clustering methods blindly combine the information from multi-view(More)
Multitask learning (MTL) aims at improving the generalization performance of multiple tasks by exploiting the shared factors among them. An important line of research in the MTL is the robust MTL (RMTL) methods, which use trace-norm regularization to capture task relatedness via a low-rank structure. The existing algorithms for the RMTL optimization(More)
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