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[P]: spectralGraphTopology an R package for learning graphs from data via spectral constraints

spectralGraphTopology provides estimators to learn k-component, bipartite, and k-component bipartite graphs from data by imposing spectral constraints on the eigenvalues and eigenvectors of the Laplacian and adjacency matrices. Those estimators leverages spectral properties of the graphical models as a prior information, which turn out to play key roles in unsupervised machine learning tasks such as community detection.

spectralGraphTopology is developed on GitHub: https://github.com/dppalomar/spectralGraphTopology

For documentation, installation instructions, and examples of usage, check out https://mirca.github.io/spectralGraphTopology

submitted by /u/jvmirca
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.