7 papers
The Power of Bias: Optimizing Client Selection in Federated Learning with Heterogeneous Differential Privacy
Jiating Ma, Yipeng Zhou, Qi Li +3
To preserve the data privacy, the federated learning (FL) paradigm emerges in which clients only expose model gradients rather than original data for conducting model training. To…
Optimizing Mobile-Friendly Viewport Prediction for Live 360-Degree Video Streaming
Lei Zhang, Tao Long, Weizhen Xu +2
Viewport prediction is the crucial task for adaptive 360-degree video streaming, as the bitrate control algorithms usually require the knowledge of the user's viewing portions of t…
Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression
Xiaoxin Su, Yipeng Zhou, Laizhong Cui +1
Recently, federated learning (FL) has gained momentum because of its capability in preserving data privacy. To conduct model training by FL, multiple clients exchange model updates…
Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes
Xiaoxin Su, Yipeng Zhou, Laizhong Cui +2
In Federated Learning (FL) paradigm, a parameter server (PS) concurrently communicates with distributed participating clients for model collection, update aggregation, and model di…
A Fast Blockchain-based Federated Learning Framework with Compressed Communications
Laizhong Cui, Xiaoxin Su, Yipeng Zhou
Recently, blockchain-based federated learning (BFL) has attracted intensive research attention due to that the training process is auditable and the architecture is serverless avoi…
Magic ELF: Image Deraining Meets Association Learning and Transformer
Kui Jiang, Zhongyuan Wang, Chen Chen +3
Convolutional neural network (CNN) and Transformer have achieved great success in multimedia applications. However, little effort has been made to effectively and efficiently harmo…