Consistent nonparametric estimation for heavy-tailed sparse graphs
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Publication:2054468
DOI10.1214/20-AOS1985zbMath1486.62080arXiv1508.06675OpenAlexW3204583332MaRDI QIDQ2054468
Shirshendu Ganguly, Henry Cohn, Christian Borgs, Jennifer T. Chayes
Publication date: 3 December 2021
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1508.06675
Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05) Random graphs (graph-theoretic aspects) (05C80) Probabilistic graphical models (62H22)
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Cites Work
- Unnamed Item
- Unnamed Item
- Pseudo-likelihood methods for community detection in large sparse networks
- Rate-optimal graphon estimation
- Variational Bayes model averaging for graphon functions and motif frequencies inference in \(W\)-graph models
- Universally consistent vertex classification for latent positions graphs
- Convergent sequences of dense graphs. II. Multiway cuts and statistical physics
- Oracle inequalities for network models and sparse graphon estimation
- Random graphs with a given degree sequence
- Spectral clustering and the high-dimensional stochastic blockmodel
- The method of moments and degree distributions for network models
- Limits of dense graph sequences
- Convergent sequences of dense graphs. I: Subgraph frequencies, metric properties and testing
- Quick approximation to matrices and applications
- Representations for partially exchangeable arrays of random variables
- Multivariate sampling and the estimation problem for exchangeable arrays
- Estimation and prediction for stochastic blockmodels for graphs with latent block structure
- The Metropolis algorithm for graph bisection
- An \(L^{p}\) theory of sparse graph convergence. II: LD convergence, quotients and right convergence
- Matrix estimation by universal singular value thresholding
- Consistency of spectral clustering in stochastic block models
- Moments of two-variable functions and the uniqueness of graph limits
- Co-clustering separately exchangeable network data
- Measure preserving transformations and rearrangements
- Stochastic blockmodels with a growing number of classes
- A nonparametric view of network models and Newman–Girvan and other modularities
- Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions
- Achieving Exact Cluster Recovery Threshold via Semidefinite Programming
- Exact Recovery in the Stochastic Block Model
- The solution of some random NP-hard problems in polynomial expected time
- Mixed membership stochastic blockmodels
- Graph Partitioning via Adaptive Spectral Techniques
- Graph limits and exchangeable random graphs
- Metrics for sparse graphs
- Latent Space Approaches to Social Network Analysis
- A Simple SVD Algorithm for Finding Hidden Partitions
- Generic Sample Splitting for Refined Community Recovery in Degree Corrected Stochastic Block Models
- Stochastic Blockmodels for Directed Graphs
- An 𝐿^{𝑝} theory of sparse graph convergence I: Limits, sparse random graph models, and power law distributions
- Community detection thresholds and the weak Ramanujan property
- Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown
- Graphons, cut norm and distance, couplings and rearrangements
- The phase transition in inhomogeneous random graphs
- Spectral Clustering by Recursive Partitioning