A survey on model-based co-clustering: high dimension and estimation challenges

Cites Work

Model-based clustering based on sparse finite Gaussian mixtures
Model selection for Gaussian latent block clustering with the integrated classification likelihood
Likelihood-based model selection for stochastic block models
Model-based clustering of time series in group-specific functional subspaces
Model-based clustering of multivariate ordinal data relying on a stochastic binary search algorithm
Variable selection for model-based clustering using the integrated complete-data likelihood
Modeling heterogeneity in random graphs through latent space models: a selective review
Variable selection for latent class analysis with application to low back pain diagnosis
The discriminative functional mixture model for a comparative analysis of bike sharing systems
Asymptotic normality of maximum likelihood and its variational approximation for stochastic blockmodels
Spectral clustering and the high-dimensional stochastic blockmodel
Block clustering with collapsed latent block models
Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
Variable selection in model-based clustering: a general variable role modeling
Exact and Monte Carlo calculations of integrated likelihoods for the latent class model
Constrained monotone EM algorithms for finite mixture of multivariate Gaussians
Block clustering with Bernoulli mixture models: comparison of different approaches
Degeneracy in the maximum likelihood estimation of univariate Gaussian mixtures with EM.
Model-based clustering of high-dimensional data: a review
Mutual information, phi-squared and model-based co-clustering for contingency tables
Model-based co-clustering for ordinal data
Variable selection methods for model-based clustering
Consistency of maximum-likelihood and variational estimators in the stochastic block model
Auto-weighted multi-view co-clustering with bipartite graphs
Comparing high-dimensional partitions with the Co-clustering adjusted rand index
Learning from missing data with the binary latent block model
Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance
Co-clustering of multivariate functional data for the analysis of air pollution in the south of France
Consistency and asymptotic normality of latent block model estimators
Generalized co-clustering analysis via regularized alternating least squares
Model-based co-clustering for mixed type data
Convergence of the groups posterior distribution in latent or stochastic block models
Estimation and model selection for model-based clustering with the conditional classification likelihood
Defining probability density for a distribution of random functions
The latent topic block model for the co-clustering of textual interaction data
Variable selection in model-based clustering and discriminant analysis with a regularization approach
Model-based clustering
Hierarchical clustering with discrete latent variable models and the integrated classification likelihood
Functional non-parametric latent block model: a multivariate time series clustering approach for autonomous driving validation
Component Elimination Strategies to Fit Mixtures of Multiple Scale Distributions
Mixture Densities, Maximum Likelihood and the EM Algorithm
Degeneracy in the Maximum Likelihood Estimation of Univariate Gaussian Mixtures for Grouped Data and Behaviour of the EM Algorithm
Finding Groups in Data
Model-Based Gaussian and Non-Gaussian Clustering
Stochastic versions of the em algorithm: an experimental study in the mixture case
Dealing With Label Switching in Mixture Models
Community structure in social and biological networks
Community Detection and Stochastic Block Models
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions
New Consistent and Asymptotically Normal Parameter Estimates for Random-Graph Mixture Models
10.1162/jmlr.2003.3.4-5.993
Exploratory latent structure analysis using both identifiable and unidentifiable models
Co-Clustering of Ordinal Data via Latent Continuous Random Variables and Not Missing at Random Entries
Estimating the components of a mixture of normal distributions
Model-Based Clustering and Classification for Data Science
Estimation and selection for the latent block model on categorical data
Parameter-wise co-clustering for high-dimensional data
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item

This page was built for publication: A survey on model-based co-clustering: high dimension and estimation challenges