Info-Clustering: A Mathematical Theory for Data Clustering

2016/05/04 by Chung Chan, Chan, Chung, Ali Al-Bashabsheh +7
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Bayesian Methods and Mixture Models #Complex Network Analysis Techniques #FOS: Biological sciences #FOS: Computer and information sciences #Gene expression and cancer classification #Genomics (q-bio.GN) #Information Theory (cs.IT) #Neurons and Cognition (q-bio.NC)

paper · pdf · doi:10.48550/arxiv.1605.01233

openalex publication_date 2016/05/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We formulate an info-clustering paradigm based on a multivariate information measure, called multivariate mutual information, that naturally extends Shannon's mutual information between two random variables to the multivariate case involving more than two random variables. With proper model reductions, we show that the paradigm can be applied to study the human genome and connectome in a more meaningful way than the conventional algorithmic approach. Not only can info-clustering provide justifications and refinements to some existing techniques, but it also inspires new computationally feasible solutions.

Citations

• Parallel Correlation Clustering on Big Graphs
• Information theory, multivariate dependence, and genetic network inference
• On Information and Sufficiency
• Communication Theory of Secrecy Systems*
• Discovering Structure in High-Dimensional Data Through Correlation\n Explanation
• Network attributes for segregation and integration in the human brain
• The structure of the nervous system of the nematode Caenorhabditis elegans
• ImageNet classification with deep convolutional neural networks

Related

• Hierarchical Clustering Based on Mutual Information
• Hierarchical Clustering Using Mutual Information
• MIC: Mutual Information based hierarchical Clustering
• Information based clustering: Supplementary material
• Info-Clustering: An Efficient Algorithm by Network Information Flow