WebHaozhao Wang, Yichen Li, Wenchao Xu, Ruixuan Li, Yufeng Zhan, and Zhigang Zeng, "DaFKD: Domain-aware Federated Knowledge Distillation," in Proc. of CVPR, 2024. 2024 Liwen Yang, Yuanqing Xia*, Xiaopu Zhang, Lingjuan Ye, and Yufeng Zhan *, "Classification-Based Diverse Workflows Scheduling in Clouds," IEEE Transactions on Automation …
Group Knowledge Transfer:Federated Learning of Large CNNs at …
WebFeb 3, 2024 · In this paper, we propose a novel federated learning scheme (Fig. 3), FedDKD, which introduces a module of decentralized knowledge distillation (DKD) to … WebOct 25, 2024 · Federated learning is a new scheme of distributed machine learning, which enables a large number of edge computing devices to jointly learn a shared model … property tax act nsw
(PDF) Federated Knowledge Distillation - ResearchGate
WebNov 4, 2024 · Federated Knowledge Distillation. Distributed learning frameworks often rely on exchanging model parameters across workers, instead of revealing their raw data. A prime example is federated … Webpropose FedHKD (Federated Hyper-Knowledge Distillation), a novel FL algo-rithm in which clients rely on knowledge distillation (KD) to train local models. In particular, each client extracts and sends to the server the means of local data representations and the corresponding soft predictions – information that we refer to as “hyper ... WebNov 24, 2024 · To address this problem, we propose a heterogenous Federated learning framework based on Bidirectional Knowledge Distillation (FedBKD) for IoT system, which integrates knowledge distillation into the local model upload (client-to-cloud) and global model download (cloud-to-client) steps of federated learning. property tax accountant brisbane