Web: http://arxiv.org/abs/2201.09965

Jan. 26, 2022, 2:10 a.m. | Pedro Valdeira, Cláudia Soares, João Xavier

cs.LG updates on arXiv.org arxiv.org

Expectation Maximization (EM) is the standard method to learn Gaussian
mixtures. Yet its classic, centralized form is often infeasible, due to privacy
concerns and computational and communication bottlenecks. Prior work dealt with
data distributed by examples, horizontal partitioning, but we lack a
counterpart for data scattered by features, an increasingly common scheme (e.g.
user profiling with data from multiple entities). To fill this gap, we provide
an EM-based algorithm to fit Gaussian mixtures to Vertically Partitioned data
(VP-EM). In federated …

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