Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

Alzheimer's disease (AD) is the most common form of dementia, characterized by
progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic …

Even if measuring the outcome of binary classifications is a pivotal task in machine learning
and statistics, no consensus has been reached yet about which statistical rate to employ to …

In recent years, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful
technique for investigating cellular heterogeneity and structure. However, analyzing scRNA …

Many human languages have words for emotions such as “anger” and “fear,” yet it is not
clear whether these emotions have similar meanings across languages, or why their …

The proliferation of single-cell multimodal sequencing technologies has enabled us to
understand cellular heterogeneity with multiple views, providing novel and actionable …

This paper proposes a novel contrastive learning framework, called FOCAL, for extracting
comprehensive features from multimodal time-series sensing signals through self …

Bitcoin is quickly emerging as a popular digital payment system. However, in spite of its
reliance on pseudonyms, Bitcoin raises a number of privacy concerns due to the fact that all …

Information theoretic based measures form a fundamental class of similarity measures for
comparing clusterings, beside the class of pair-counting based and set-matching based …

Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale
of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable …