The label noise is a serious problem limiting the performance of federated learning.
According to the performance evaluation for the trained federated models, data selection …

With the enormous amount of data growing exponentially, data owners aim to share data
with each other to acquire an enhanced analytic view of their data. Distributed association …

The application of artificial intelligence models to raw multimedia data is susceptible to
various data inference attacks, posing a significant risk in terms of sensitive input information …

Traffic flow prediction is an important part of intelligent transportation systems (ITS).
However, sensor failures or the transmission distortion often occur in the process of data …

In recent years, Local differential privacy (LDP), as a strong privacy preserving methodology,
has been widely deployed in real world applications. It allows the users to perturb their data …

When 5G began its commercialisation journey around 2020, the discussion on the vision of
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …

With the fast development of artificial intelligence (eg, deep learning), it brings the new
opportunities and challenges for business management and service optimization of the …

With the development of technology, the use of big data is spreading at an increasing rate.
The issues of storing, analysing and securing data have brought along the methods that …

Deep Learning and Machine Learning algorithms are popularly used in the healthcare
sector for diagnosis with many algorithms have been successfully implemented to perform …