This article studies the derivatives in models that flexibly characteriz...
The 6th generation (6G) wireless communication network is envisaged to b...
The 6th generation (6G) wireless networks will likely to support a varie...
With the standardization and commercialization completed at an unforesee...
Deploying active reflecting elements at the intelligent reflecting surfa...
Stochastic gradient descent (SGD) is a scalable and memory-efficient
opt...
Deep learning has gained huge empirical successes in large-scale
classif...
Magnetic soft robots have attracted growing interest due to their unique...
Ordinary differential equations (ODEs) are widely used to model complex
...
Stochastic gradient descent (SGD) and projected stochastic gradient desc...
When data is of an extraordinarily large size or physically stored in
di...
With both the standardization and commercialization completed in an
unfo...
Research on speaker recognition is extending to address the vulnerabilit...
In massive data analysis, training and testing data often come from very...
The endogeneity issue is fundamentally important as many empirical
appli...
A new statistical procedure, based on a modified spline basis, is propos...
Deep neural network is a state-of-art method in modern science and
techn...
Statistical inference based on lossy or incomplete samples is of fundame...
Many complex networks in real world can be formulated as hypergraphs whe...