In this paper, we propose Federated Ensemble Learning (FEL) as a solution to address the large memory requirement for recommendation systems subject to label ...
Dec 31, 2022 · Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. Download PDF.
Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. Authors: Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis ...
Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems . Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis,. Kiwan Maeng ...
Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. M Hejazinia, D Huba, I Leontiadis, K Maeng, M Malek, L Melis ...
Jun 7, 2022 · To increase the effective learning capacity of FL in the Label-only Privacy case, we propose a new approach, Federated Ensemble Learning (FEL).
Dec 2, 2024 · We propose Federated Ensemble Learning (FEL) as a solution to tackle the large memory requirement of deep learning ranking and recommendation ...
Dec 20, 2024 · A wide range of federated learning approaches have been proposed to train models locally at each client without sharing their sensitive data, ...
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Dec 2, 2024 · Federated learning, an emerging distributed machine learning approach, has garnered increasing attention in the field of data security and ...
In this research, we propose a hybrid Federated Ensemble-Learning (FedEL) model to detect transportation modes in VEN, which improves federated strategies in ...