Data and Channel-Adaptive Sensor Scheduling for Federated Edge Learning via Over-the-Air Gradient Aggregation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3096570
Abstract: Over-the-air gradient aggregation and data-aware scheduling have recently drawn great attention due to the outstanding performance in improving communication efficiency for federated edge learning applications. However, in this case, the estimated gradient suffers from the… read more here.
Keywords: federated edge; gradient aggregation; data channel; air gradient ... See more keywords
Channel-Estimation-Free Gradient Aggregation for Over-the-Air SIMO Federated Learning
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DOI: 10.1109/lwc.2024.3382498
Abstract: We study the gradient aggregation in over-the-air federated learning (OA-FL), where the parameter server (PS) uses a combining vector to estimate the aggregated gradient. We propose a novel channel-estimation-free (CE-Free) gradient aggregation scheme for OA-FL,… read more here.
Keywords: aggregation air; gradient aggregation; federated learning; aggregation ... See more keywords
Boosting the Transferability of Adversarial Examples Through Gradient Aggregation
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DOI: 10.1109/tifs.2025.3574989
Abstract: Deep neural networks(DNNs) have been demonstrated to be vulnerable to meticulously crafted adversarial examples. Transfer-based attacks do not require access to the target model’s information, have emerged as a substantial threat to the deployment of… read more here.
Keywords: loss; gradient aggregation; adversarial examples; aware loss ... See more keywords
ALEPH: Accelerating Distributed Training With eBPF-Based Hierarchical Gradient Aggregation
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DOI: 10.1109/tnet.2024.3404999
Abstract: Distributed training includes two important operations: gradient transmission and gradient aggregation, which will consume massive bandwidth and computing resources. To achieve efficient distributed training, one must overcome two critical challenges: heterogeneity of bandwidth resources and… read more here.
Keywords: gradient aggregation; ebpf; distributed training;