Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...
The Gulf Research Program (GRP) of the National Academies of Sciences, Engineering, and Medicine today announced an award of more than $7.3 million to support four interdisciplinary research projects ...
Abstract: Multivariate data contain an abundance of information and many techniques have been proposed to allow humans to navigate this information in an ordered fashion. For this work, we focus on ...
Abstract: Multivariate Time Series (MTS) forecasting is to accurately predict future trends through in-depth analysis of historical time series data, and to provide valuable reference to support for ...
Background Low socioeconomic status (SES) is linked to increased cardiovascular risk, but its association with carotid atherosclerosis in the general population is less well studied. We examined ...
This study investigated the dynamics of human cortical network activity with functional magnetic resonance imaging during movie watching and studied the modulation of these dynamics by subcortical ...
Mathematicians are still trying to understand fundamental properties of the Fourier transform, one of their most ubiquitous ...
Graphene is a two-dimensional material consisting of a single layer of carbon atoms arranged in a honeycomb structure. Its properties include high strength and good conductivity of heat and ...
Principal component analysis summarizes high dimensional data into a few dimensions. Each dimension is called a principal component and represents a linear combination of the variables. The first ...
Objective Concentration of care and collaborations between hospitals increasingly reorganise oncological care into Comprehensive Cancer Networks (CCNs), aiming to improve care outcomes and reduce ...
The final, formatted version of the article will be published soon. Continuous traumatic stress has wide-ranging implications for important life outcomes across multiple domains. We present the design ...
Mathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to ...
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