May 8, 2023 · Our approach allows to build an ensemble composed of different local models, which are trained in a distributed way on different client devices.
May 8, 2023 · In this paper we present Ensemble and Continual Federated Learning, a federated architecture based on ensemble techniques for solving continual ...
In this paper we present Ensemble and Continual Federated Learning, a federated architecture based on ensemble techniques for solving continual classification ...
Ensemble and continual federated learning for classification tasks - RUC
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In this paper we present Ensemble and Continual Federated Learning, a federated architecture based on ensemble techniques for solving continual classification ...
Jun 12, 2020 · Federated learning is a popular framework that allows multiple distributed devices to train models remotely, collaboratively, and preserving data privacy.
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Ensemble and continual federated learning for classification tasks
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Ensemble and continual federated learning for classification tasks ; ISSN · 0885-6125 ; Ano de publicación · 2023 ; Volume · 112 ; Número · 9 ; Páxinas · 3413-3453.
Jul 11, 2024 · This paper presents a federated random forest approach that employs a novel ensemble construction method aimed at improving performance under non-IID data.
Oct 23, 2023 · Continual federated learning (CFL) is a setting where each client receives a continual stream of data and federated learning is periodically ...
In this work, we systematically define the main sources of new knowledge in FL, including new features, tasks, models, and algorithms.
Additionally, the ensemble solution appropriately classifies the data as a consequence of the voting performed by the individual models' accurate predictions.
Missing: continual | Show results with:continual