Accurate Tensor Completion via Adaptive Low-Rank Representation
Accurate Tensor Completion via Adaptive Low-Rank Representation
Low-rank representation-based approaches that assume low-rank tensors and exploit their low-rank structure with appropriate prior models have underpinned much of the recent progress in tensor completion. However, real tensor data only approximately comply with the low-rank requirement in most cases, viz., the tensor consists of low-rank (e.g., principle part) as …