Machine learning (ML) has succeeded in improving our daily routines by enabling
automation and improved decision making in a variety of industries such as healthcare …

Federated learning (FL) is a cutting-edge artificial intelligence approach. It is a decentralized
problem-solving technique that allows users to train using massive data. Unprocessed …

Software Engineering (SE) researchers are extensively applying Large Language Models
(LLMs) to address challenges in SE tasks such as code clone detection, code …

The fifth generation (5G) of telecommunications networks is currently commercially
deployed. One of their core enabling technologies is cellular Massive Multiple-Input-Multiple …

Federated Learning (FL) is a new machine learning paradigm that enables training models
collaboratively across clients without sharing private data. In FL, data is non-uniformly …

In recent years, there has been a rapid increase in the integration of Internet of Things (IoT)
systems into edge computing. This integration offers several advantages over traditional …

To solve the data silos and data security dilemma faced by machine learning (ML), the
concept of federated learning (FL) was first proposed, and federated learning has also …

Federated Learning (FL) is a new machine learning paradigm that enables training models
collaboratively across clients without sharing private data. In FL, data is non-uniformly …

Federated learning (FL) is a cutting-edge artificial intelligence approach. It is a decentralized
problem-solving technique that allows users to train using massive data. Unprocessed …

To support large-scale machine learning, distributed training is a promising approach as
large-scale machine learning is both resource and time consuming. Machine-Learning-as-a …