We study the tensor robust principal component analysis (TRPCA) problem,...
Tensor completion is an important problem in modern data analysis. In th...
While uniform sampling has been widely studied in the matrix completion
...
Developing large-scale distributed methods that are robust to the presen...
Classification and topic modeling are popular techniques in machine lear...
Heat diffusion processes have found wide applications in modelling dynam...
In this paper, we consider the problem of recovery of a burst-like forci...
We study the problem of tensor robust principal component analysis (TRPC...
Low rank tensor approximation is a fundamental tool in modern machine
le...
This paper considers the use of Robust PCA in a CUR decomposition framew...
Robust principal component analysis (RPCA) is a widely used tool for
dim...
A dataset of COVID-19-related scientific literature is compiled, combini...
In our paper, we have studied the tensor completion problem when the sam...
Matrix completion, the problem of completing missing entries in a data m...
This article studies how to form CUR decompositions of low-rank matrices...
The CUR decomposition is a factorization of a low-rank matrix obtained b...
This note discusses an interesting matrix factorization called the CUR
D...
This article discusses a useful tool in dimensionality reduction and low...