Fedconv: A learning-on-model paradigm for heterogeneous federated clients

L Shen, Q Yang, K Cui, Y Zheng, XY Wei… - Proceedings of the 22nd …, 2024 - dl.acm.org
Federated Learning (FL) facilitates collaborative training of a shared global model without
exposing clients' private data. In practical FL systems, clients (eg, edge servers …

Communication optimization techniques in Personalized Federated Learning: Applications, challenges and future directions

F Sabah, Y Chen, Z Yang, A Raheem, M Azam… - Information …, 2025 - Elsevier
Abstract Personalized Federated Learning (PFL) aims to train machine learning models on
decentralized, heterogeneous data while preserving user privacy. This research survey …

Pfdrl: Personalized federated deep reinforcement learning for residential energy management

J Gao, W Wang, F Nikseresht… - Proceedings of the …, 2023 - dl.acm.org
The rise of the Internet of Things (IoT) has increased standby energy consumption due to the
growing number of smart devices in homes. Existing approaches use real-time energy data …

Multi-sensor Data Privacy Protection with Adaptive Privacy Budget for IoT Systems

X Liu, Y Zheng, Z Li, Y Hu - 2024 IEEE Conference on …, 2024 - ieeexplore.ieee.org
In the era of pervasive sensing and data-driven decision-making, the Internet of Things (IoT)
has become ubiquitous, with sensors serving as the fundamental building blocks of IoT …

Twofer: Ambiguous Transmissions for Low-Latency Sensor Networks Facing Noise, Privacy and Loss

J Oostvogels, S Michiels… - 2024 23rd ACM/IEEE …, 2024 - ieeexplore.ieee.org
Today's wireless sensor networks focus on achieving reliable data transfer over a lossy
medium at the expense of latency. However, sensor data are often noisy and thus only …

FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems

J Gao, Y Li - 2024 IEEE International Conference on …, 2024 - ieeexplore.ieee.org
Personalized medication aims to tailor healthcare to individual patient characteristics.
However, the heterogeneity of patient data across healthcare systems presents significant …

Federated Learning with Knowledge Distillation to Mitigate Catastrophic Forgetting and Data Heterogeneity in IoV Systems

J Wang, J Gao - 2024 IEEE International Conference on Big …, 2024 - ieeexplore.ieee.org
In Internet of Vehicles (IoV), intelligent transportation recognition is key to smart
transportation systems. However, training models using data from individual vehicles often …