3 citations · 4 across the 5 of their papers we have counts for
5 papers
Improved Quantization Strategies for Managing Heavy-tailed Gradients in Distributed Learning
Guangfeng Yan, Tan Li, Yuanzhang Xiao +2
Gradient compression has surfaced as a key technique to address the challenge of communication efficiency in distributed learning. In distributed deep learning, however, it is obse…
Towards Quantum-Safe Federated Learning via Homomorphic Encryption: Learning with Gradients
Guangfeng Yan, Shanxiang Lyu, Hanxu Hou +2
This paper introduces a privacy-preserving distributed learning framework via private-key homomorphic encryption. Thanks to the randomness of the quantization of gradients, our lea…
Generalized Simple Regenerating Codes: Trading Sub-packetization and Fault Tolerance
Zhengyi Jiang, Hao Shi, Zhongyi Huang +3
Maximum distance separable (MDS) codes have the optimal trade-off between storage efficiency and fault tolerance, which are widely used in distributed storage systems. As typical n…
Update Bandwidth for Distributed Storage
Zhengrui Li, Sian-Jheng Lin, Po-Ning Chen +2
In this paper, we consider the update bandwidth in distributed storage systems~(DSSs). The update bandwidth, which measures the transmission efficiency of the update process in DSS…
Cauchy MDS Array Codes With Efficient Decoding Method
Hanxu Hou, Yunghsiang S. Han
Array codes have been widely used in communication and storage systems. To reduce computational complexity, one important property of the array codes is that only XOR operation is…