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20162026
most citedA Survey on Privacy-Preserving Caching at Network Edge: Classification, Solutions, and Challenges

22 citations · 64 across the 34 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.NI2023★ 1 cited

cRVR: A Stackelberg Game Approach for Joint Privacy-Aware Video Requesting and Edge Caching

Xianzhi Zhang, Linchang Xiao, Yipeng Zhou +4

As users conveniently stream their favorite online videos, video request records are automatically stored by video content providers, which have a high chance of privacy leakage. U…

cs.LG2023★ 4 cited

pFedSim: Similarity-Aware Model Aggregation Towards Personalized Federated Learning

Jiahao Tan, Yipeng Zhou, Gang Liu +2

The federated learning (FL) paradigm emerges to preserve data privacy during model training by only exposing clients' model parameters rather than original data. One of the biggest…

cs.LG2023

A Survey of Federated Evaluation in Federated Learning

Behnaz Soltani, Yipeng Zhou, Venus Haghighi +1

In traditional machine learning, it is trivial to conduct model evaluation since all data samples are managed centrally by a server. However, model evaluation becomes a challenging…

cs.LG2023

BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learning

Yunchao Yang, Yipeng Zhou, Miao Hu +2

Federated learning (FL) is a prospective distributed machine learning framework that can preserve data privacy. In particular, cross-silo FL can complete model training by making i…

cs.LG2023

FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment

Jiahao Liu, Jiang Wu, Jinyu Chen +3

Different from conventional federated learning, personalized federated learning (PFL) is able to train a customized model for each individual client according to its unique require…

cs.DC2023★ 6 cited

Edge-Based Video Analytics: A Survey

Miao Hu, Zhenxiao Luo, Amirmohammad Pasdar +3

Edge computing has been getting a momentum with ever-increasing data at the edge of the network. In particular, huge amounts of video data and their real-time processing requiremen…