The Council has approved conclusions calling on member states to take into account the interplay between housing needs and ...

Abstract: In this article, we propose a general framework for the unsupervised fuzzy rule-based dimensionality reduction primarily for data visualization. This framework has the following important ...

This paper evaluates three approaches to address parameter proliferation issue in nowcasting: (i) variable selection using adjusted stepwise autoregressive integrated moving average with exogenous ...

Causal inference has been increasingly essential in modern observational studies with rich covariate information. However, it is often challenging to estimate the causal effect with high-dimensional ...

DREiMac is a library for topological data coordinatization, visualization, and dimensionality reduction. Currently, DREiMac is able to find topology-preserving representations of point clouds taking ...

Multivariable Mendelian randomisation (MVMR) is an instrumental variable technique that generalises the MR framework for multiple exposures. Framed as a regression problem, it is subject to the ...

The development of genomic selection (GS) methods has allowed plant breeding programs to select favorable lines using genomic data before performing field trials. Improvements in genotyping technology ...

We seek to use dimensionality reduction to simplify the difficult task of controlling a lower limb prosthesis. Though many techniques for dimensionality reduction have been described, it is not clear ...

The processes involved in decision-making, such as deliberation on sensory evidence and the preparation and execution of motor actions, are thought to emerge from the coordinated dynamics within and ...