Clustering multivariate count data via Dirichlet-multinomial network fusion

DOI10.1016/j.csda.2022.107634OpenAlexW4304996045MaRDI QIDQ6166908

Wei Lin, Unnamed Author, Jing-Ru Zhang

Publication date: 7 July 2023

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2022.107634

zbMATH Keywords

overdispersiontext analysisconvex clusteringnonasymptotic error boundexponential family approximationgroup \(L_1\) fusion

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Cites Work

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• Douglas-Rachford splitting for nonconvex optimization with application to nonconvex feasibility problems
• Hanson-Wright inequality and sub-Gaussian concentration
• Statistical properties of convex clustering
• Text classification from labeled and unlabeled documents using EM
• Stochastic backward Euler: an implicit gradient descent algorithm for \(k\)-means clustering
• Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
• Mixtures of Dirichlet-multinomial distributions for supervised and unsupervised classification of short text data
• A mixture model approach to spectral clustering and application to textual data
• Pairwise Variable Selection for High-Dimensional Model-Based Clustering
• Cluster Analysis
• Extended Bayesian information criteria for model selection with large model spaces
• Introduction to Information Retrieval
• Dynamical Processes on Complex Networks
• Mixture models and exploratory analysis in networks
• Convex Clustering via l  1 Fusion Penalization
• 10.1162/jmlr.2003.3.4-5.993
• Sparsity and Smoothness Via the Fused Lasso
• Recovering Trees with Convex Clustering
• Scalable estimation and regularization for the logistic normal multinomial model
• Fast unfolding of communities in large networks
• Collective dynamics of ‘small-world’ networks
• Model-Based Clustering and Classification for Data Science

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