Community detection and stochastic block models: recent developments

E Abbe - Journal of Machine Learning Research, 2018‏ - jmlr.org
The stochastic block model (SBM) is a random graph model with planted clusters. It is widely
employed as a canonical model to study clustering and community detection, and provides …

A comprehensive review of community detection in graphs

J Li, S Lai, Z Shuai, Y Tan, Y Jia, M Yu, Z Song, X Peng… - Neurocomputing, 2024‏ - Elsevier
The study of complex networks has significantly advanced our understanding of community
structures which serves as a crucial feature of real-world graphs. Detecting communities in …

[کتاب][B] Modern algorithms of cluster analysis

ST Wierzchoń, MA Kłopotek - 2018‏ - Springer
This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …

Spectral clustering and the high-dimensional stochastic blockmodel

K Rohe, S Chatterjee, B Yu - 2011‏ - projecteuclid.org
Networks or graphs can easily represent a diverse set of data sources that are characterized
by interacting units or actors. Social networks, representing people who communicate with …

[کتاب][B] Statistical analysis of network data with R

ED Kolaczyk, G Csárdi - 2014‏ - Springer
Networks and network analysis are arguably one of the largest growth areas of the early
twenty-first century in the quantitative sciences. Despite roots in social network analysis …

Spectral graph theory

D Spielman - Combinatorial scientific computing, 2012‏ - api.taylorfrancis.com
Spectral graph theory is the study and exploration of graphs through the eigenvalues and
eigenvectors of matrices naturally associated with those graphs. It is intuitively related to …

Spectral graph theory and its applications

DA Spielman - 48th Annual IEEE Symposium on Foundations …, 2007‏ - ieeexplore.ieee.org
Spectral graph theory is the study of the eigenvalues and eigenvectors of matrices
associated with graphs. In this tutorial, we will try to provide some intuition as to why these …

[کتاب][B] Descriptive vs. inferential community detection in networks: Pitfalls, myths and half-truths

TP Peixoto - 2023‏ - cambridge.org
Community detection is one of the most important methodological fields of network science,
and one which has attracted a significant amount of attention over the past decades. This …

Random walk graph Laplacian-based smoothness prior for soft decoding of JPEG images

X Liu, G Cheung, X Wu, D Zhao - IEEE Transactions on Image …, 2016‏ - ieeexplore.ieee.org
Given the prevalence of joint photographic experts group (JPEG) compressed images,
optimizing image reconstruction from the compressed format remains an important problem …

[کتاب][B] Algorithms for sparse linear systems

J Scott, M Tůma - 2023‏ - library.oapen.org
Large sparse linear systems of equations are ubiquitous in science, engineering and
beyond. This open access monograph focuses on factorization algorithms for solving such …