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Fedconv: A learning-on-model paradigm for heterogeneous federated clients
Federated Learning (FL) facilitates collaborative training of a shared global model without
exposing clients' private data. In practical FL systems, clients (eg, edge servers …
exposing clients' private data. In practical FL systems, clients (eg, edge servers …
Communication optimization techniques in Personalized Federated Learning: Applications, challenges and future directions
Abstract Personalized Federated Learning (PFL) aims to train machine learning models on
decentralized, heterogeneous data while preserving user privacy. This research survey …
decentralized, heterogeneous data while preserving user privacy. This research survey …
Pfdrl: Personalized federated deep reinforcement learning for residential energy management
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 …
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
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 …
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
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 …
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
Personalized medication aims to tailor healthcare to individual patient characteristics.
However, the heterogeneity of patient data across healthcare systems presents significant …
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 …
transportation systems. However, training models using data from individual vehicles often …