Info-Clustering: A Mathematical Theory for Data Clustering Academic Article

abstract

• 2017 IEEE. 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.

authors

• Liu, Tie

published proceedings

• IEEE Transactions on Molecular Biological and Multi-Scale Communications

author list (cited authors)

• Chan, C., Al-Bashabsheh, A., Zhou, Q., Kaced, T., & Liu, T.

citation count

• 20

complete list of authors

• Chan, Chung||Al-Bashabsheh, Ali||Zhou, Qiaoqiao||Kaced, Tarik||Liu, Tie

publication date

• January 2016

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Molecular Biological and Multi-Scale Communications  Journal

keywords

• Genetics
• Human Genome

Digital Object Identifier (DOI)

• 10.1109/tmbmc.2016.2630054

start page

• 64

end page

• 91

volume

• 2

issue

• 1

URL

• http://dx.doi.org/10.1109/tmbmc.2016.2630054