@inproceedings{f57786884031471482a5cd7798510647,
title = "Inference of hidden structures in complex physical systems by multi-scale clustering",
abstract = "We survey the application of a relatively newbranch of statistical physics— “community detection”—to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the quest of partitioning a complex system involving many elements into optimally decoupled subsets or communities of such elements. We review a multiresolution variant which is used to ascertain structures at different spatial and temporal scales. Significant patterns are obtained by examining the correlations between different independent solvers. Similar to other combinatorial optimization problems in the NP complexity class, community detection exhibits several phases. Typically, illuminating orders are revealed by choosing parameters that lead to extremal information theory correlations.",
author = "Z. Nussinov and P. Ronhovde and Dandan Hu and S. Chakrabarty and Bo Sun and Mauro, \{Nicholas A.\} and Sahu, \{Kisor K.\}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; International Conference on Information Science for Materials Discovery and Design, 2014 ; Conference date: 04-02-2014 Through 07-02-2014",
year = "2015",
doi = "10.1007/978-3-319-23871-5\_6",
language = "English",
isbn = "9783319238708",
series = "Springer Series in Materials Science",
publisher = "Springer Verlag",
pages = "115--138",
editor = "Turab Lookman and Krishna Rajan and Alexander, \{Francis J.\}",
booktitle = "Information Science for Materials Discovery and Design",
}