Results 81 to 90 of about 2,509 (175)

On the Foundational Arguments of Sufficient Dimension Reduction

WIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley   +1 more source

Text Mining in Bibliometrics and Science Mapping: A Methodological Review

WIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Text mining has become a foundational component of contemporary bibliometrics and science mapping, enabling systematic analysis of the semantic structure, thematic evolution, and cognitive organization of scientific fields. Integrating textual evidence with relational indicators enriches knowledge maps and supports more comprehensive, content‐sensitive
Michelangelo Misuraca
wiley   +1 more source

Parametric Model Order Reduction by Box Clustering With Applications in Mechatronic Systems

International Journal for Numerical Methods in Engineering, Volume 127, Issue 10, 30 May 2026.
ABSTRACT High temperatures and structural deformations can compromise the functionality and reliability of new components for mechatronic systems. Therefore, high‐fidelity simulations (HFS) are employed during the design process, as they enable a detailed analysis of the thermal and structural behavior of the system.
Juan Angelo Vargas‐Fajardo, Diana Manvelyan‐Stroot, Catharina Czech, Pietro Botazzoli, Fabian Duddeck   +4 more
wiley   +1 more source

An optimization approach for dynamical Tucker tensor approximation

Results in Applied Mathematics, 2019
An optimization-based approach for Tucker tensor approximation of parameter-dependent data tensors and solutions of tensor differential equations with low Tucker rank is presented.
Lukas Exl
doaj   +1 more source

Superposition of Doppler‐Shifting Magnetopause Kelvin‐Helmholtz Modes Through Dynamic Mode Decomposition of a Global MHD Simulation

Geophysical Research Letters, Volume 53, Issue 10, 28 May 2026.
Abstract The Kelvin‐Helmholtz instability (KHI) mediates the viscous‐like solar‐terrestrial interaction by generating magnetopause surface waves that quickly become non‐linear. Basic theory predicts the locally most‐unstable linear wave dominates.
H. M. Kelly, M. O. Archer, J. P. Eastwood, M. Heyns, J. W. B. Eggington, J. P. Chittenden   +5 more
wiley   +1 more source

A Hypercomplex Tensor-SVD and Its Application

A Hypercomplex Tensor-SVD and Its Application
identifier:oai:t2r2.star.titech.ac.jp ...
Takehiko Mizoguchi, Isao Yamada
openaire   +2 more sources

Handling the Non-smooth Challenge in Tensor SVD: A Multi-objective Tensor Recovery Framework

Recently, numerous tensor singular value decomposition (t-SVD)-based tensor recovery methods have shown promise in processing visual data, such as color images and videos. However, these methods often suffer from severe performance degradation when confronted with tensor data exhibiting non-smooth changes.
Jingjing Zheng, Wanglong Lu, Wenzhe Wang, Yankai Cao, Xiaoqin Zhang 0002, Xianta Jiang   +5 more
openaire   +2 more sources

Lower serum uric acid and impairment of right cerebral hemisphere structural brain networks are related to depressive symptoms in cerebral small vessel disease: A cross-sectional study

Heliyon
Cerebral small vessel disease (SVD) may be associated with an increased risk of depressive symptoms. Serum uric acid (SUA), an antioxidant, may be involved in the occurrence and development of depressive symptoms, but the mechanism remains unknown ...
Lei Yu, Ming Yi, Jiayu Guo, Jinbiao Li, Huixing Zeng, Liqian Cui, Xiangming Xu, Gang Liu, Yuhua Fan, Jinsheng Zeng, Shihui Xing, Yicong Chen, Meng Wang, Shuangquan Tan, Leow Yi Jin, Dilip Kumar, Ashwati Vipin, Soo See Ann, Fatin Zahra Binte Zailan, Gurveen Kaur Sandhu, Nagaendran Kandiah, Chao Dang   +21 more
doaj   +1 more source

Randomized block Krylov method for approximation of truncated tensor SVD

Journal of the Franklin Institute
This paper is devoted to studying the application of the block Krylov subspace method for approximation of the truncated tensor SVD (T-SVD). The theoretical results of the proposed randomized approach are presented. Several experimental experiments using synthetics and real-world data are conducted to verify the efficiency and feasibility of the ...
Malihe Nobakht Kooshkghazi, Salman Ahmadi-Asl, André L.F. de Almeida   +2 more
openaire   +2 more sources

A mixed EIM-SVD tensor decomposition for bivariate functions

, 2017
In this paper we present a mixed EIM-SVD tensor decomposition for bivariate functions. This method is composed, as its name suggests, of two main steps. The first one, provides an approximate representation of a function $f$ in separate form by the use of a Tensor Empirical Interpolation Method (TEIM). The second phase consists in applying the Singular
De Vuyst, Florian, Toumi, Asma
openaire   +2 more sources