Sep 22, 2023 · In this paper, we propose a multi-task learning and Federated Learning approach for training multi-task models for encrypted traffic classification.
Our proposed two-stage federated multi-task learning scheme, pFedDAMT, aims to address data heterogeneity by first obtaining a global multi-task model that ...
In this paper, we propose a multi-task learning and Federated Learning approach for training multi-task models for encrypted traffic classification in a privacy ...
A Personalized Federated Multi-task Learning Scheme for Encrypted Traffic Classification · Xueyu GuanRun DuXiaohan WangHaipeng Qu. Computer Science ...
A Personalized Federated Multi-task Learning Scheme for Encrypted Traffic Classification · Xueyu Guan · Run Du · Xiaohan Wang · Haipeng Qu.
Personalized federated learning is employed in autonomous vehicles based on a correlated differential privacy. Correlated differential privacy is used to ensure ...
Apr 11, 2024 · Qu, “A personalized federated multi- task learning scheme for encrypted traffic classification,” in Artificial. Neural Networks and Machine ...
C. Xueyu Guan, Run Du, Xiaohan Wang, Haipeng Qu A Personalized Federated Multi-task Learning Scheme for Encrypted Traffic Classification.ICANN (3) 2023: 258- ...
Jan 3, 2025 · With the advancement of federated learning (FL), there is a growing demand for schemes that support multi-task learning on multi-modal data ...
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A hierarchical framework combined split learning and federated learning. Compatible with heterogeneous network traffic data classification model.