Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data. (arXiv:2203.01752v1 [cs.LG])

Despite enormous research interest and rapid application of federated
learning (FL) to various areas, existing studies mostly focus on supervised
federated learning under the horizontally partitioned local dataset setting.
This paper will study the unsupervised FL under the vertically partitioned
dataset setting. Accordingly, we propose the federated principal component
analysis for vertically partitioned dataset (VFedPCA) method, which reduces the
dimensionality across the joint datasets over all the clients and extracts the
principal component feature information for downstream data analysis. We …

analysis arxiv data distributed distributed data extension kernel