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08/15/2023
NeFL: Nested Federated Learning for Heterogeneous Clients
Federated learning (FL) is a promising approach in distributed learning ...
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05/23/2023
Transceiver Design and Performance Analysis for LR-FHSS-based Direct-to-Satellite IoT
This paper presents a novel transceiver design aimed at enabling Direct-...
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10/29/2022
Fast-Convergent Federated Learning via Cyclic Aggregation
Federated learning (FL) aims at optimizing a shared global model over mu...
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10/29/2022
Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance
While being an effective framework of learning a shared model across mul...
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09/14/2022
Compressed Particle-Based Federated Bayesian Learning and Unlearning
Conventional frequentist FL schemes are known to yield overconfident dec...
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11/23/2021
Forget-SVGD: Particle-Based Bayesian Federated Unlearning
Variational particle-based Bayesian learning methods have the advantage ...
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04/08/2021
Bayesian Variational Federated Learning and Unlearning in Decentralized Networks
Federated Bayesian learning offers a principled framework for the defini...
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03/24/2021
Meta-ViterbiNet: Online Meta-Learned Viterbi Equalization for Non-Stationary Channels
Deep neural networks (DNNs) based digital receivers can potentially oper...
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03/03/2020
End-to-End Fast Training of Communication Links Without a Channel Model via Online Meta-Learning
When a channel model is not available, the end-to-end training of encode...
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02/03/2020
Cooperative Learning via Federated Distillation over Fading Channels
Cooperative training methods for distributed machine learning are typica...
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01/05/2020
From Learning to Meta-Learning: Reduced Training Overhead and Complexity for Communication Systems
Machine learning methods adapt the parameters of a model, constrained to...
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10/22/2019
Meta-Learning to Communicate: Fast End-to-End Training for Fading Channels
When a channel model is available, learning how to communicate on fading...
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08/23/2019
Learning to Demodulate from Few Pilots via Offline and Online Meta-Learning
This paper considers an Internet-of-Things (IoT) scenario in which devic...
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07/05/2019
Wireless Federated Distillation for Distributed Edge Learning with Heterogeneous Data
Cooperative training methods for distributed machine learning typically ...
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03/06/2019
Learning How to Demodulate from Few Pilots via Meta-Learning
Consider an Internet-of-Things (IoT) scenario in which devices transmit ...
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01/16/2019