Low-rank tensor completion aims to recover the missing entries of multi-way data, which has
become popular and vital in many fields such as signal processing and computer vision. It …

With the powerful ability to exploit the latent structure of self-representation information,
multiple off-the-shelf low rank tensor constraints have been employed in multiview tensor …

With powerful ability to exploit latent structure of self-representation information, different
tensor decompositions have been employed into low rank multi-view clustering (LRMVC) …