Geometric deep learning is an umbrella term for emerging techniques attempting to generalize (structured) deep neural models to non-Euclidean domains, such as graphs and manifolds. The purpose of this ...

This paper presents a novel adaptive synthetic (ADASYN) sampling approach for learning from imbalanced data sets. The essential idea of ADASYN is to use a weighted distribution for different minority ...

We define hybrid intelligence (HI) as the combination of human and machine intelligence, augmenting human intellect and capabilities instead of replacing them and achieving goals that were unreachable ...

In this article, we introduce an Internet of Things application, smart community, which refers to a paradigmatic class of cyber-physical systems with cooperating objects (i.e., networked smart homes).

In this paper, supereigenvalue and constrained supereigenvalue problems of an addition-min fuzzy matrix are investigated. In a peer-to-peer file sharing system, the download requirement of the ...

This note studies the global robust output regulation problem for a class of nonlinear systems by an output-based event-triggered control law. First, we convert the problem into the event-triggered ...