Denoising and Completion of 3D Data via Multidimensional Dictionary Learning

no code implementations • 31 Dec 2015 • Zemin Zhang, Shuchin Aeron

In this paper a new dictionary learning algorithm for multidimensional data is proposed.

Dictionary Learning Image Denoising

Exact tensor completion using t-SVD

no code implementations • 16 Feb 2015 • Zemin Zhang, Shuchin Aeron

Using this factorization one can derive notion of tensor rank, referred to as the tensor tubal rank, which has optimality properties similar to that of matrix rank derived from SVD.

Matrix Completion

Novel methods for multilinear data completion and de-noising based on tensor-SVD

2 code implementations • CVPR 2014 • Zemin Zhang, Gregory Ely, Shuchin Aeron, Ning Hao, Misha Kilmer

Based on t-SVD, the notion of multilinear rank and a related tensor nuclear norm was proposed in [11] to characterize informational and structural complexity of multilinear data.

Novel Factorization Strategies for Higher Order Tensors: Implications for Compression and Recovery of Multi-linear Data

no code implementations • 2 Jul 2013 • Zemin Zhang, Gregory Ely, Shuchin Aeron, Ning Hao, Misha Kilmer

In this paper we propose novel methods for compression and recovery of multilinear data under limited sampling.

Data Compression Tensor Decomposition