Online nonnegative and sparse canonical polyadic decomposition of fluorescence tensors
Abstract The NonNegative Canonical Polyadic Decomposition (NN-CPD) is used in many
fields such as in chemistry, biology and medicine. The data coming from these fields can be …
fields such as in chemistry, biology and medicine. The data coming from these fields can be …
Globally convergent Jacobi-type algorithms for simultaneous orthogonal symmetric tensor diagonalization
In this paper, we consider a family of Jacobi-type algorithms for a simultaneous orthogonal
diagonalization problem of symmetric tensors. For the Jacobi-based algorithm of [M. Ishteva …
diagonalization problem of symmetric tensors. For the Jacobi-based algorithm of [M. Ishteva …
Accelerating probabilistic tensor canonical polyadic decomposition with nonnegative factors: An inexact BCD Approach
Recently, Bayesian modeling and variational inference (VI) were leveraged to enable the
nonnegative factor matrix learning with automatic rank determination in tensor canonical …
nonnegative factor matrix learning with automatic rank determination in tensor canonical …
Online nonnegative canonical polyadic decomposition: Algorithms and application
IW Sanou, R Redon, X Luciani… - 2021 29th European …, 2021 - ieeexplore.ieee.org
The Nonnegative Canonical Polyadic Decomposition (NN-CPD) is now widely used in
signal processing to decompose multi-way arrays thanks to nonnegative factor matrices. In …
signal processing to decompose multi-way arrays thanks to nonnegative factor matrices. In …
A Primal-Dual algorithm for nonnegative N-th order CP tensor decomposition: application to fluorescence spectroscopy data analysis
K El Qate, M El Rhabi, A Hakim, E Moreau… - … Systems and Signal …, 2022 - Springer
This work concerns the resolution of inverse problems encountered in multidimensional
signal processing problems. Here, we address the problem of tensor decomposition, more …
signal processing problems. Here, we address the problem of tensor decomposition, more …
Online Canonical Polyadic Decomposition: Application of Fluorescence Tensors with Nonnegative Orthogonality and Sparse Constraint
The canonical polyadic decomposition (CPD) is now widely used in signal processing to
decompose multi-way arrays. In many applications, it is important to add constraints to …
decompose multi-way arrays. In many applications, it is important to add constraints to …
A parallel strategy for an evolutionary stochastic algorithm: application to the CP decomposition of nonnegative N-th order tensors
S Laura, C Prissette, S Maire… - 2020 28th European …, 2021 - ieeexplore.ieee.org
In this article, we address the problem of the Canonical Polyadic decomposition (aka CP,
Candecomp or Parafac decomposition) of N-th order tensors that can be very large. In our …
Candecomp or Parafac decomposition) of N-th order tensors that can be very large. In our …
Sparse nonnegative CANDECOMP/PARAFAC decomposition in block coordinate descent framework: A comparison study
Nonnegative CANDECOMP/PARAFAC (NCP) decomposition is an important tool to process
nonnegative tensor. Sometimes, additional sparse regularization is needed to extract …
nonnegative tensor. Sometimes, additional sparse regularization is needed to extract …
Decomposition of large nonnegative tensors using memetic algorithms with application to environmental data analysis
In this article, we address the problem of the Canonical Polyadic decomposition (or
Candecomp/Parafac Decomposition) of large N-way tensors under nonnegativity …
Candecomp/Parafac Decomposition) of large N-way tensors under nonnegativity …
Computation of the nonnegative canonical tensor decomposition with two accelerated proximal gradient algorithms
Multidimensional signal analysis has become an important part of many signal processing
problems. This type of analysis allows to take advantage of different diversities of a signal in …
problems. This type of analysis allows to take advantage of different diversities of a signal in …