Collaborative inference has been a promising solution to enable
resource...
Federated continual learning (FCL) learns incremental tasks over time fr...
In this work, we investigate the challenging problem of on-demand federa...
Federated learning (FL) enables mobile devices to collaboratively learn ...
Federated learning (FL) over mobile devices has fostered numerous intrig...
As a promising method of central model training on decentralized device ...
Federated learning (FL) enables devices in mobile edge computing (MEC) t...
Federated learning (FL), an emerging distributed machine learning paradi...
The continuous convergence of machine learning algorithms, 5G and beyond...
Recent advances in machine learning, wireless communication, and mobile
...
Federated learning (FL) is a new paradigm for large-scale learning tasks...
Deep learning has attracted broad interest in healthcare and medical
com...
(Gradient) Expectation Maximization (EM) is a widely used algorithm for
...
Sparse learning is a very important tool for mining useful information a...
The Alternating Direction Method of Multipliers (ADMM) and its distribut...
Millimeter wave (mmWave) communications can potentially meet the high
da...
Machine learning is increasingly becoming a powerful tool to make decisi...
Due to massive amounts of data distributed across multiple locations,
di...
In this paper, we study the resource allocation problem for a cooperativ...
Secure communication is a promising technology for wireless networks bec...
In cognitive radio networks (CRNs), spectrum trading is an efficient way...