When

Start: 11/13/2013 - 4:15pm

End : 11/13/2013 - 5:15pm

End : 11/13/2013 - 5:15pm

Category

Colloquium

Speaker

Blake Hunter, University of California at Los Angeles

Abstract

There has been increasing demand to understand the data around us. The flood of social media requires new mathematics, methodologies and procedures to extract knowledge from massive datasets. Spectral methods are numerical linear algebra graph based techniques that use eigenfunctions of a graph to extract the underlying global structure of a dataset. The construction of these, application dependent, graphs require new mathematical ideas that extend data represen- tation, distance, topic modeling and sparsity. The product is often massive matrices that push the limits of matrix computation. This talk looks at content based search with applications to analyzing documents, Twitter microblogs, images and hyperspectral images.

Where

Davidson Lecture Hall, Claremont McKenna College

Attachment | Size |
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Hunter.pdf | 104.5 KB |

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