Rapid advances in artificial intelligence (AI) in the last decade have been largely built upon
the wide applications of deep learning (DL). However, the high carbon footprint yielded by …

At present, there is a pressing need for data scientists and academic researchers to devise
advanced machine learning and artificial intelligence-driven systems that can effectively …

This Research work addresses the pressing need within cloud computing for a trust-based
service mechanism that effectively manages the burgeoning volume and variety of data …

The rapidly evolving field of cloud-based data sharing faces critical challenges in ensuring
comprehensive privacy protection and trust for both data producers and seekers. Current …

The rapid adoption of cloud-based data sharing is transforming collaboration across various
sectors, yet ensuring trust and privacy in sensitive data remains a critical challenge. This …

Abstract Graph Neural Networks (GNNs) are one of the primary methods for molecular
property prediction due to their ability to learn state-of-the-art level representations from …

Background: After entering the new millennium, computer-aided diagnosis (CAD) is rapidly
developing as an emerging technology worldwide. Expanding the spectrum of CAD-related …

As a new paradigm of machine learning, green learning has achieved performance
comparable to deep learning in vision tasks, knowledge graph learning, and modeling …

Modern machine learning algorithms aim to extract fine-grained information from data to
provide accurate predictions, which often conflicts with the goal of privacy protection. This …

Deepfake techniques can generate realistic fake images and videos. Malicious fake facial
images quickly spread through the Internet, posing a potential threat to personal privacy and …