Tensor completion has been widely used in computer vision and machine learning. Most existing tensor completion methods empirically assume the intrinsic tensor is simultaneous low-rank in all over modes. However, tensor data recorded ...
Clustering is a fundamental learning task with many applications in a wide range of fields. Recently proposed techniques have shown that performing clustering in a discriminative space provides reliable results. Motivated by these ...
Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based ...
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