With the emerging developments of the Metaverse, a virtual world where people can
interact, socialize, play, and conduct their business, it has become critical to ensure that the …

Mobile Edge Computing (MEC) has been a promising paradigm for communicating and
edge processing of data on the move. We aim to employ Federated Learning (FL) and …

The Metaverse, a 3-dimensional virtual realm mirroring real-world objects, promises
transformative experiences. Its potential is tempered by data collection, confidentiality, and …

Federated learning enables multiple users to collaboratively train a global model using the
users' private data on users' local machines. This way, users are not required to share their …

Quantum federated learning (QFL) is a novel framework that integrates the advantages of
classical federated learning (FL) with the computational power of quantum technologies …

Post-quantum security is critical in the quantum era. Quantum computers, along with
quantum algorithms, make the standard cryptography based on RSA or ECDSA over FL or …

Quantum Federated Learning (QFL) is an emerging interdisciplinary field that merges the
principles of Quantum Computing (QC) and Federated Learning (FL), with the goal of …

The emerging metaverses can be regarded as the current wave of the digital civilization
revolution due to it build a new connection between the physical and virtual space, and such …

As the development of quantum computing hardware is on the rise, its potential application
to various research areas has been investigated, including to machine learning. Recently …

Advanced artificial intelligence techniques, such as federated learning, has been applied to
broad areas, eg, image classification, speech recognition, smart city, and healthcare …