Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with
different features about the same set of users jointly train machine learning models without …

Hypergraphs have attracted increasing attention in recent years thanks to their flexibility in
naturally modeling a broad range of systems where high-order relationships exist among …

Cluster analysis finds groups in data automatically. Most methods have been heuristic and
leave open such central questions as: how many clusters are there? Which method should I …

Abstract The Principal Component Analysis (PCA) is a widely used method of reducing the
dimensionality of high-dimensional data, often followed by visualizing two of the …

Artificial intelligence (AI) technology is sweeping the globe, leading to bold statements by
notable figures:“[AI] is going to change the world more than anything in the history of …

Clustering by fast search and find of density peaks (DPC) is a new clustering method that
was reported in Science in June 2014. This clustering algorithm is based on the assumption …

Breast cancer is a significant public health concern worldwide, and early detection is crucial
for its treatment. Although breast cancer has been extensively studied, there is still room for …

In this article, we propose an optimal method referred to as SPlit for splitting a dataset into
training and testing sets. SPlit is based on the method of support points (SP), which was …

Digital pathology represents one of the major evolutions in modern medicine. Pathological
examinations constitute the gold standard in many medical protocols, and also play a critical …

In this study, a new predictive framework is proposed by integrating an improved grey wolf
optimization (IGWO) and kernel extreme learning machine (KELM), termed as IGWO‐KELM …