An Approximation of the Integrated Classification Likelihood for the Latent Block Model

No abstract is available for this paper.

• Publication year

  2012

• Venue

  2012 IEEE 12th International Conference on Data Mining Workshops

• Publication date

  2012-12-10

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/ICDMW.2012.32
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Model selection for the binary latent block model

  2012cited by this paper
• Convergence of the groups posterior distribution in latent or stochastic block models

  2012cited by this paper
• Block clustering with collapsed latent block models

  2010cited by this paper
• A Bayesian approach to two-mode clustering

  2009cited by this paper
• Selecting Among Multi-Mode Partitioning Models of Different Complexities: A Comparison of Four Model Selection Criteria

  2008cited by this paper
• Algorithms for Model-based Block Gaussian Clustering

  2008cited by this paper
• Clustering with block mixture models

  2003cited by this paper
• Assessing a Mixture Model for Clustering with the Integrated Completed Likelihood

  2000cited by this paper
• How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis

  1998cited by this paper

• The Dynamic Latent Block Model for Sparse and Evolving Count Matrices

  2020cites this paper
• PhD position in Data Science & Artificial Intelligence Latent Data Models for Large-Scale Clustering

  2018cites this paper
• Advanced mixtures for complex high dimensional data : from model-based to Bayesian non-parametric inference Advanced mixtures for complex high dimensional data : from model-based to Bayesian non-parametric inference

  2015cites this paper
• Revue des méthodes pour la classification jointe des lignes et des colonnes d'un tableau

  2015cites this paper
• Estimation et sélection de modèle pour le modèle des blocs latents

  2014cites this paper
• Artificial Intelligence Latent Data Models for Large-Scale Clustering

  year unknowncites this paper