Sample-Starved Large Scale Network Analysis

: In this research project we developed correlation mining methods to answer the following fundamental question about complex networks: What are the fundamental limits on the amount of information that can be inferred about a network from a small number n of indirect empirical observations? In these terms, the overall objective was to develop algorithms and establish performance limits for mining information from correlation networks. The focus was on the sample starved regime arises when the number of variables (columns of the correlation matrix) is of the same order or larger than the number of observations available to estimate or detect patterns in the matrix.