arXiv Machine Learning
Oct 3

Degree-Corrected Joint Matrix Factorization for Multilayer Community Detection

The paper introduces a degree‑corrected joint matrix factorization technique for detecting communities in multilayer networks. It uses a nonnegative symmetric matrix trifactorization that enforces disjoint, shared communities across layers while allowing each layer to have distinct connectivity patterns and node degrees. An efficient algorithm is presented and evaluated on a multilayer degree‑corrected stochastic block model, showing superior performance compared to existing methods.

By Alexandra Dache, Manon Rustin, Arnaud Vandaele, Nicolas Gillis
arXiv Machine Learning
Aug 20

Transportable Causal Effect Estimation across Networks under Interference

The paper introduces TranCE, a doubly‑robust algorithm for estimating causal effects when an intervention is applied to one network but the interest lies in another, differing network. By extending selection diagrams to capture covariate and structural network shifts, the authors derive transport formulas for direct, spillover, and total effects, and validate the method on semi‑synthetic social‑network benchmarks and a real weather‑insurance field experiment.

By Xiaojing Du, Jiuyong Li, Lin Liu, Debo Cheng, Jixue Liu, Thuc Duy Le