Impact of regularization on spectral clustering
From MaRDI portal
Publication:309744
DOI10.1214/16-AOS1447zbMath1357.62229arXiv1312.1733OpenAlexW2464534118MaRDI QIDQ309744
Publication date: 7 September 2016
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1312.1733
regularizationnetwork analysiscommunity detectionstochastic block modelregularized spectral clustering (RSC)
Multivariate analysis (62H99) Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05)
Related Items
Hierarchical Community Detection by Recursive Partitioning, Community Detection in Sparse Networks Using the Symmetrized Laplacian Inverse Matrix (SLIM), A review on spectral clustering and stochastic block models, Asymptotically efficient estimators for stochastic blockmodels: the naive MLE, the rank-constrained MLE, and the spectral estimator, Impact of regularization on spectral clustering, Randomized Spectral Clustering in Large-Scale Stochastic Block Models, Community detection by \(L_{0}\)-penalized graph Laplacian, Unnamed Item, Modularity Maximization for Graphons, Large volatility matrix analysis using global and national factor models, Fast Network Community Detection With Profile-Pseudo Likelihood Methods, Unnamed Item, Unnamed Item, Estimating mixed-memberships using the symmetric Laplacian inverse matrix, Spectral Clustering via Adaptive Layer Aggregation for Multi-Layer Networks, Estimating a network from multiple noisy realizations, Spectral clustering in the dynamic stochastic block model, Unnamed Item, Unnamed Item, Unnamed Item, On semidefinite relaxations for the block model, Fusing data depth with complex networks: community detection with prior information, Minimax rates in network analysis: graphon estimation, community detection and hypothesis testing, Community detection in sparse networks via Grothendieck's inequality, Limit theorems for eigenvectors of the normalized Laplacian for random graphs, Analysis of spectral clustering algorithms for community detection: the general bipartite setting, Unnamed Item, Enhanced Equivalence Projective Simulation: A Framework for Modeling Formation of Stimulus Equivalence Classes, Role of normalization in spectral clustering for stochastic blockmodels, Graph Powering and Spectral Robustness, Detecting Overlapping Communities in Networks Using Spectral Methods
Cites Work
- Unnamed Item
- Pseudo-likelihood methods for community detection in large sparse networks
- Impact of regularization on spectral clustering
- Spectral clustering and the high-dimensional stochastic blockmodel
- On the convergence to equilibrium of Kac's random walk on matrices
- Matrix concentration inequalities via the method of exchangeable pairs
- A nonparametric view of network models and Newman–Girvan and other modularities
- Improved Spectral-Norm Bounds for Clustering
- Community structure in social and biological networks
- A Consistent Adjacency Spectral Embedding for Stochastic Blockmodel Graphs
- Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
- Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown
- Improved Cheeger's inequality