Web: http://arxiv.org/abs/2206.07975

June 17, 2022, 1:10 a.m. | Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, Bin Cui

cs.LG updates on arXiv.org arxiv.org

Due to the rising concerns on privacy protection, how to build machine
learning (ML) models over different data sources with security guarantees is
gaining more popularity. Vertical federated learning (VFL) describes such a
case where ML models are built upon the private data of different participated
parties that own disjoint features for the same set of instances, which fits
many real-world collaborative tasks. Nevertheless, we find that existing
solutions for VFL either support limited kinds of input features or suffer …

arxiv data learning lg machine machine learning

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