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07/17/2023
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels
Many existing FL methods assume clients with fully-labeled data, while i...
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05/30/2022
To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning
Federated learning (FL) facilitates collaboration between a group of cli...
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04/27/2022
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
Federated learning (FL) enables edge-devices to collaboratively learn a ...
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09/16/2021
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer
Personalized federated learning (FL) aims to train model(s) that can per...
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12/14/2020
Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning
Due to communication constraints and intermittent client availability in...
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10/03/2020
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
Federated learning is a distributed optimization paradigm that enables a...
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05/11/2018
V2X Downlink Coverage Analysis with a Realistic Urban Vehicular Model
As the realization of vehicular communication such as vehicle-to-vehicle...
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01/22/2018
RF Lens-Embedded Antenna Array for mmWave MIMO: Design and Performance
The requirement of high data-rate in the fifth generation wireless syste...
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11/24/2017
