LANS Informal Seminar: Daniel Dunlavy

Seminar Title: Multiway data analysis using tensor decompositions
Speaker: Daniel Dunlavy, Senior Technical Staff, Sandia National Laboratories

Date/Time: 2010-10-06 15:00
Location: Bldg 240 Rm 4301

Description:
We will discuss the problem of factorizing multi-way data sets with the goal of capturing the underlying latent structure of the data. Such data can be represented using tensors, or multidimensional arrays, and latent structure can be exposed using low-rank factorizations, akin to principal component analysis used in two-way data analysis. Focus will be on one of the most well-known tensor factorizations, CANDECOMP/PARAFAC (CP), one of the higher order analogs of the singular value decomposition. Discussion will include scalability and robustness of various methods for computing CP factorizations, and application of these factorizations in the areas of chemometrics, citation analysis, network traffic analysis, and neuroscience will be demonstrated. This is joint work with Tamara G. Kolda, Evrim Acar , Brett Bader and Morten Mørup.