Research Output per year
Personal profile
Research interests
My main area of research is domain decomposition methods for solving large-scale problems in massively parallel environments.
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
Lagrange multiplier Method
Mathematics
Lagrange multipliers
Engineering & Materials Science
Domain Decomposition Method
Mathematics
Preconditioner
Mathematics
Domain decomposition methods
Engineering & Materials Science
Condition number
Mathematics
GMRES
Mathematics
Elliptic PDE
Mathematics
Co Author Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2008 2018
Comparisons among several methods for handling missing data in principal component analysis (PCA)
Loisel, S. & Takane, Y., 18 Jan 2018, In : Advances in Data Analysis and Classification.Research output: Contribution to journal › Article
principal component analysis
comparison
method
rate
An optimal Schwarz preconditioner for a class of parallel adaptive finite elements
Loisel, S. & Nguyen, H., Sep 2017, In : Journal of Computational and Applied Mathematics. 321, p. 90–107 18 p.Research output: Contribution to journal › Article
Open Access
File
Adaptive Finite Elements
Preconditioner
Mesh
Smallest Eigenvalue
Largest Eigenvalue
A comparison of additive schwarz preconditioners for parallel adaptive finite elements
Loisel, S. & Nguyen, T. H., 2016, Domain Decomposition Methods in Science and Engineering XXII. Springer International Publishing, p. 345-354 10 p. (Lecture Notes in Computational Science and Engineering; vol. 104)Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
On the PLS algorithm for multiple regression (PLS1)
Takane, Y. & Loisel, S., 16 Oct 2016, The Multiple Facets of Partial Least Squares and Related Methods. Springer, p. 17-28 12 p. (Springer Proceedings in Mathematics & Statistics; vol. 173)Research output: Chapter in Book/Report/Conference proceeding › Chapter
Partial Least Squares
Least Square Algorithm
Multiple Regression
Least Squares Estimator
Dimensionality
Schwarz preconditioner for the stochastic finite element method
Subber, W. & Loisel, S., 2016, Domain Decomposition Methods in Science and Engineering XXII. Springer, p. 397-405 9 p. (Lecture Notes in Computational Science and Engineering; vol. 104)Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Stochastic Finite Element
Polynomial Chaos
Stochastic Methods
Chaos theory
Preconditioner