Distributed learning in wireless networks: Recent progress and future challenges

M Chen, D Gündüz, K Huang, W Saad… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
The next-generation of wireless networks will enable many machine learning (ML) tools and
applications to efficiently analyze various types of data collected by edge devices for …

Federated learning in smart cities: Privacy and security survey

R Al-Huthaifi, T Li, W Huang, J Gu, C Li - Information Sciences, 2023 - Elsevier
Over the last decade, smart cities (SC) have been developed worldwide. Implementing big
data and the internet of things improves the monitoring and integration of different …

Communication-efficient and distributed learning over wireless networks: Principles and applications

J Park, S Samarakoon, A Elgabli, J Kim… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Machine learning (ML) is a promising enabler for the fifth-generation (5G) communication
systems and beyond. By imbuing intelligence into the network edge, edge nodes can …

Privacy for free: Wireless federated learning via uncoded transmission with adaptive power control

D Liu, O Simeone - IEEE Journal on Selected Areas in …, 2020 - ieeexplore.ieee.org
Federated Learning (FL) refers to distributed protocols that avoid direct raw data exchange
among the participating devices while training for a common learning task. This way, FL can …

Optimized power control design for over-the-air federated edge learning

X Cao, G Zhu, J Xu, Z Wang… - IEEE Journal on Selected …, 2021 - ieeexplore.ieee.org
Over-the-air federated edge learning (Air-FEEL) has emerged as a communication-efficient
solution to enable distributed machine learning over edge devices by using their data locally …

Cooperative and competitive multi-agent systems: From optimization to games

J Wang, Y Hong, J Wang, J Xu, Y Tang… - IEEE/CAA Journal of …, 2022 - ieeexplore.ieee.org
Multi-agent systems can solve scientific issues related to complex systems that are difficult or
impossible for a single agent to solve through mutual collaboration and cooperation …

A comprehensive survey of v2x cybersecurity mechanisms and future research paths

R Sedar, C Kalalas, F Vázquez-Gallego… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Recent advancements in vehicle-to-everything (V2X) communication have notably improved
existing transport systems by enabling increased connectivity and driving autonomy levels …

Over-the-Air Computation for 6G: Foundations, Technologies, and Applications

Z Wang, Y Zhao, Y Zhou, Y Shi, C Jiang… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
The rapid advancement of artificial intelligence technologies has given rise to diversified
intelligent services, which place unprecedented demands on massive connectivity and …

Xor mixup: Privacy-preserving data augmentation for one-shot federated learning

MJ Shin, C Hwang, J Kim, J Park, M Bennis… - arXiv preprint arXiv …, 2020 - arxiv.org
User-generated data distributions are often imbalanced across devices and labels,
hampering the performance of federated learning (FL). To remedy to this non-independent …

Private retrieval, computing, and learning: Recent progress and future challenges

S Ulukus, S Avestimehr, M Gastpar… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Most of our lives are conducted in the cyberspace. The human notion of privacy translates
into a cyber notion of privacy on many functions that take place in the cyberspace. This …