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MathBio Seminar

Friday, February 1, 2013 - 11:00am

Aaditya Rangan



University of Pennsylvania

Lynch 318

Adi is also giving the AMCS colloquium in Towne 337 are 2:00 on "Emergent dynamics in a model of the visual cortex"

Title: Efficient methods for detecting low-rank substructure

Abstract: A common goal in data-analysis is to capture some subset of the data using a reduced number of degrees-of-freedom. For example, when analyzing genomic data one is often interested in discovering subgroups of genes which exhibit correlated activity across a subset of patients. This goal can be rephrased as follows: given a large data matrix in a high-dimensional space, how can one efficiently determine if some submatrix is well captured using only a few principal components? Naive methods for solving this problem are either very slow, or do not scale well as the size of the matrix increases. In this talk I will present a method that is quite fast, and practical even when the data sets are very large.