Kai Yue

College of Engineering

Works (2)

Updated: April 5th, 2024 15:25

2022 journal article

Communication-Efficient Federated Learning via Predictive Coding

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 16(3), 369–380.

By: K. Yue n, R. Jin n, C. Wong n & H. Dai n

author keywords: Predictive models; Servers; Collaborative work; Predictive coding; Entropy coding; Costs; Quantization (signal); Federated learning; distributed optimization; predictive coding
TL;DR: This paper proposes a predictive coding based compression scheme for federated learning that has shared prediction functions among all devices and allows each worker to transmit a compressed residual vector derived from the reference. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: May 31, 2022

2022 article

Federated Learning via Plurality Vote

Yue, K., Jin, R., Wong, C.-W., & Dai, H. (2022, December 7). IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, Vol. 12.

By: K. Yue n, R. Jin*, C. Wong n & H. Dai n

author keywords: Distributed optimization; efficient communication; federated learning; neural network quantization
TL;DR: This work proposes a new scheme named federated learning via plurality vote (FedVote), which can reduce quantization error and converges faster compared to the methods directly quantizing the model updates. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: January 9, 2023

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