Maximum Likelihood Estimation on Stochastic Blockmodels for Directed Graph Clustering
This paper studies the directed graph clustering problem through the lens of statistics, where
we formulate clustering as estimating underlying communities in the directed stochastic …
we formulate clustering as estimating underlying communities in the directed stochastic …
Clustering for directed graphs using parametrized random walk diffusion kernels
Clustering based on the random walk operator has been proven effective for undirected
graphs, but its generalization to directed graphs (digraphs) is much more challenging …
graphs, but its generalization to directed graphs (digraphs) is much more challenging …
Geometries of mixed graphs/networks in complex vector spaces
E Estrada - 2024 - hal.science
This paper thoroughly introduces several geometric measures for mixed graphs represented
by complex-valued Hermitian adjacency matrices. We define the communicability functions …
by complex-valued Hermitian adjacency matrices. We define the communicability functions …
Antidiagonal Operators, Antidiagonalization, Hollow Quasidiagonalization--Unitary, Orthogonal, Permutation, and Otherwise-and Symmetric Spectra
DR Nicholus - arxiv preprint arxiv:2304.13842, 2023 - arxiv.org
After summarizing characteristics of antidiagonal operators, we derive three direct sum
decompositions characterizing antidiagonalizable linear operators-the first up to permutation …
decompositions characterizing antidiagonalizable linear operators-the first up to permutation …