Results 131 to 140 of about 402,138 (284)

Application of regularized covariance matrices in logistic regression and portfolio optimization

Scientific Reports
Covariance estimation has widespread applications in various fields such as logistic regression and portfolio optimization. However, in high-dimensional or small-sample scenarios, traditional covariance matrix estimation often encounters the problem of ...
Fang Sun, Xiaoqing Huang
doaj   +1 more source

Return and Volatility Spillovers Among Major Cotton Markets

Agribusiness, EarlyView.
ABSTRACT This study explores return and volatility transmission among major cotton markets. Several events have disrupted cotton supply and demand in recent years, leading to heightened price volatility and significant shifts in market interconnections.
Susmitha Kalli, Berna Karali, Yangxuan Liu, Munisamy Gopinath   +3 more
wiley   +1 more source

Estimation of the signal subspace without estimation of the inverse covariance matrix [PDF]

Let a high-dimensional random vector X can be represented as a sum of two components - a signal S, which belongs to some low-dimensional subspace S, and a noise component N.
Vladimir Panov
core  

The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry

Agribusiness, EarlyView.
ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley   +1 more source

Computational study of permeability in cardboard coating layers

AIChE Journal, EarlyView.
Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman, Torben Nilsson Pingel, Niklas Lorén, Tobias Gebäck, Eva Olsson, Aila Särkkä, Magnus Röding   +6 more
wiley   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

Identification of Exhaled Volatile Organic Compounds Biomarkers for Lung Cancer Under Data‐Limited Conditions Using Data Augmentation and Multi‐View Feature Selection

Advanced Intelligent Discovery, EarlyView.
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren, Bohao Liu, Zhiyuan Qu, Xue Jiang, Heng Zhao, Danyao Qu, Ruizhi Ning, Chen Su, Taoping Liu, Guangjian Zhang, Weiwei Wu   +10 more
wiley   +1 more source

Weighted average ensemble for Cholesky-based covariance matrix estimation

Statistical Theory and Related Fields
The modified Cholesky decomposition (MCD) is an efficient technique for estimating a covariance matrix. However, it is known that the MCD technique often requires a pre-specified variable ordering in the estimation procedure.
Xiaoning Kang, Zhenguo Gao, Xi Liang, Xinwei Deng   +3 more
doaj   +1 more source