The μ-conductance measure proposed by Lovasz and Simonovits is a
size-sp...
We study a simple embedding technique based on a matrix of personalized
...
Graph clustering objective functions with tunable resolution parameters ...
Resolution parameters in graph clustering represent a size and quality
t...
Graph databases have been the subject of significant research and
develo...
Finding clusters of well-connected nodes in a graph is an extensively st...
Many clustering applications in machine learning and data mining rely on...
We present new results for LambdaCC and MotifCC, two recently introduced...
Multiple network alignment is the problem of identifying similar and rel...
We present a new framework for computing Z-eigenvectors of general tenso...
Common models for random graphs, such as Erdős-Rényi and Kronecker
graph...
Numerous algorithms are used for nonnegative matrix factorization under ...
The importance of nodes in a network constantly fluctuates based on chan...
Stochastic Kronecker graphs supply a parsimonious model for large sparse...