Web: http://arxiv.org/abs/2201.10761

Jan. 27, 2022, 2:10 a.m. | Houpu Yao, Jiazhou Wang, Peng Dai, Liefeng Bo, Yanqing Chen

cs.LG updates on arXiv.org arxiv.org

As there is a growing interest in utilizing data across multiple resources to
build better machine learning models, many vertically federated learning
algorithms have been proposed to preserve the data privacy of the participating
organizations. However, the efficiency of existing vertically federated
learning algorithms remains to be a big problem, especially when applied to
large-scale real-world datasets. In this paper, we present a fast, accurate,
scalable and yet robust system for vertically federated random forest. With
extensive optimization, we achieved …

arxiv random

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