Extends conditional entropy of heat diffusion to temporal networks, proves monotonicity, and applies a local version to change-point detection and improved community detection on synthetic benchmarks and a real school contact network.
Statistical clustering of temporal networks through a dynamic stochastic block model
3 Pith papers cite this work. Polarity classification is still indexing.
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Introduces the AR(1)-MSBM for evolving multilayer networks and provides online estimators with minimax-optimal rates and community recovery guarantees under stationarity and non-stationarity via adaptive windowing.
Two methods achieve vanishing misclassification for community detection in directed mean-field binary graphical models when T ≫ N (near-optimal), and exact recovery when T ≫ N², without knowing edge probability p.
citing papers explorer
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Conditional Entropy of Heat Diffusion on Temporal Networks
Extends conditional entropy of heat diffusion to temporal networks, proves monotonicity, and applies a local version to change-point detection and improved community detection on synthetic benchmarks and a real school contact network.
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Online Learning for Autoregressive Multilayer Stochastic Block Models under Stationarity and Non-Stationarity
Introduces the AR(1)-MSBM for evolving multilayer networks and provides online estimators with minimax-optimal rates and community recovery guarantees under stationarity and non-stationarity via adaptive windowing.
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Community detection for binary graphical models in high dimension
Two methods achieve vanishing misclassification for community detection in directed mean-field binary graphical models when T ≫ N (near-optimal), and exact recovery when T ≫ N², without knowing edge probability p.