research
∙
09/26/2022
Least-squares methods for nonnegative matrix factorization over rational functions
Nonnegative Matrix Factorization (NMF) models are widely used to recover...
share
research
∙
02/24/2022
Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image Segmentation
Convolutional Neural Networks (CNNs) with U-shaped architectures have do...
research
∙
02/23/2022
Canonical Polyadic Decomposition via the generalized Schur decomposition
The canonical polyadic decomposition (CPD) is a fundamental tensor decom...
research
∙
12/15/2021
A recursive eigenspace computation for the Canonical Polyadic decomposition
The canonical polyadic decomposition (CPD) is a compact decomposition wh...
research
∙
12/15/2021
Guarantees for existence of a best canonical polyadic approximation of a noisy low-rank tensor
The canonical polyadic decomposition (CPD) of a low rank tensor plays a ...
research
∙
06/15/2020
Nonconvex Optimization Tools for Large-Scale Matrix and Tensor Decomposition with Structured Factors
The proposed article aims at offering a comprehensive tutorial for the c...
research
∙
05/12/2020
Early soft and flexible fusion of EEG and fMRI via tensor decompositions
Data fusion refers to the joint analysis of multiple datasets which prov...
research
∙
12/10/2019
From computation to comparison of tensor decompositions
Decompositions of higher-order tensors into sums of simple terms are ubi...
research
∙
02/11/2019
Equivalent Polyadic Decompositions of Matrix Multiplication Tensors
Invariance transformations of polyadic decompositions of matrix multipli...
research
∙
12/30/2016
Double Coupled Canonical Polyadic Decomposition for Joint Blind Source Separation
Joint blind source separation (J-BSS) is an emerging data-driven techniq...
research
∙
07/06/2016