Parameterized knowledge transfer for personalized federated learning
… Heterogeneous FL and Knowledge Distillation. To enable heterogeneous model architectures
… Another way of personalization is to use Knowledge Distillation (KD) in heterogeneous FL …
… Another way of personalization is to use Knowledge Distillation (KD) in heterogeneous FL …
[HTML][HTML] Communication-efficient federated learning via knowledge distillation
… This is because in FedKD there are multiple mentor models on different decentralized
clients for personalized learning and knowledge distillation. In addition, FedKD can save up to …
clients for personalized learning and knowledge distillation. In addition, FedKD can save up to …
Metafed: Federated learning among federations with cyclic knowledge distillation for personalized healthcare
… federation can be viewed as an independent individual. To implement MetaFed, we propose
a cyclic knowledge distillation … knowledge accumulation stage and the personalization stage…
a cyclic knowledge distillation … knowledge accumulation stage and the personalization stage…
Personalized edge intelligence via federated self-knowledge distillation
… In this paper, we study personalized federated learning in which our goal is to train models
… a novel Personalized Federated Learning (PFL) framework via self-knowledge distillation, …
… a novel Personalized Federated Learning (PFL) framework via self-knowledge distillation, …
Personalized decentralized federated learning with knowledge distillation
E Jeong, M Kountouris - ICC 2023-IEEE International …, 2023 - ieeexplore.ieee.org
… However, it is generally challenging to quantify similarity under limited knowledge about …
propose a personalized and fully decentralized FL algorithm, leveraging knowledge distillation …
propose a personalized and fully decentralized FL algorithm, leveraging knowledge distillation …
Quped: Quantized personalization via distillation with applications to federated learning
… quantized and personalized models potentially having different dimensions/… of personalized
federated learning and learning quantized models; we also employ knowledge distillation …
federated learning and learning quantized models; we also employ knowledge distillation …
Spectral co-distillation for personalized federated learning
… and personalized models, we can distill the knowledge of the … benefit the training of the
personalized models. By combining … knowledge distillation to bridge the training of generic and …
personalized models. By combining … knowledge distillation to bridge the training of generic and …
[HTML][HTML] A Personalized Federated Learning Method Based on Clustering and Knowledge Distillation
J Zhang, Y Shi - Electronics, 2024 - mdpi.com
… personalized federal learning using knowledge distillation. Knowledge distillation requires
the migration of knowledge … However, in federated learning, the server cannot access the data …
the migration of knowledge … However, in federated learning, the server cannot access the data …
Data-free knowledge distillation for heterogeneous federated learning
… model using aggregated knowledge from heterogeneous users, … knowledge is not fully
utilized to guide local model learning, … a data-free knowledge distillation approach to address …
utilized to guide local model learning, … a data-free knowledge distillation approach to address …
Fedcd: Personalized federated learning via collaborative distillation
… Various challenges involved in this work include; 1) enabling knowledge distillation between
a number of clients without requiring a large pre-trained teacher network. 2) reducing the …
a number of clients without requiring a large pre-trained teacher network. 2) reducing the …
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