no code implementations • 27 Nov 2023 • Zhongyuan Lyu, Ting Li, Dong Xia
Under the mixture multi-layer stochastic block model (MMSBM), we show that the minimax optimal network clustering error rate, which takes an exponential form and is characterized by the Renyi divergence between the edge probability distributions of the component networks.
1 code implementation • 9 Feb 2023 • Ting Li, Zhongyuan Lyu, Chenyu Ren, Dong Xia
This paper develops an R package rMultiNet to analyze multilayer network data.
no code implementations • 11 Jul 2022 • Zhongyuan Lyu, Dong Xia
Comparable to GMM, the minimax optimal clustering error rate is decided by the separation strength, i. e., the minimal distance between population center matrices.
no code implementations • 22 Jan 2022 • Zhongyuan Lyu, Dong Xia
If the signal is stronger than a certain threshold, called the computational limit, we design a computationally fast estimator based on spectral aggregation and demonstrate its minimax optimality.
no code implementations • 30 Jun 2021 • Zhongyuan Lyu, Dong Xia, Yuan Zhang
We formulate the relationship between the latent positions and the observed data via a generalized multilinear kernel as the link function.
no code implementations • 10 Feb 2020 • Bing-Yi Jing, Ting Li, Zhongyuan Lyu, Dong Xia
We show that the TWIST procedure can accurately detect the communities with small misclassification error as the number of nodes and/or the number of layers increases.