Dec 14, 2022 · We explore multitask learning associated with model clustering, and first propose a clustered FMTL to achieve the multual-task learning on non-IID data.
To achieve the communication-efficiency and high accuracy with non-IID data, we propose a clustered federated multi-task learning by exploring client clustering ...
To achieve the communication-efficiency and high accuracy with non-IID data, we propose a clustered federated multi-task learning by exploring client clustering ...
Feb 20, 2024 · Abstract:The innovative Federated Multi-Task Learning (FMTL) approach consolidates the benefits of Federated Learning (FL) and Multi-Task ...
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What is non-IID data in federated learning?
What is non-IID in machine learning?
What is clustered federated learning?
Jun 29, 2024 · Clustered federated learning is a specific FL method that organizes clients into multiple groups and trains personalized models for each group [ ...
Apr 26, 2023 · This paper introduces a two-phased client selection and scheduling approach to improve the convergence speed while capturing all data distributions.
Mar 13, 2024 · Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non- ...
given the fact that in Federated Learning clients (a) can hold arbitrary non-iid data, which can not be audited by the centralized server due to privacy ...
A central problem in FL is that the data on the users' personal devices are usually non-i.i.d. Several formulations and solutions have been proposed to tackle ...
Jan 9, 2024 · We propose a federated clustered multi-domain learning algorithm based on ClusterGAN, multi-domain learning, and graph neural networks.