Semisupervised Feature Analysis by Mining Correlations Among Multiple Tasks
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DOI: 10.1109/tnnls.2016.2582746
Abstract: In this paper, we propose a novel semisupervised feature selection framework by mining correlations among multiple tasks and apply it to different multimedia applications. Instead of independently computing the importance of features for each task,… read more here.
Keywords: feature; semisupervised feature; correlations among; mining correlations ... See more keywords