### Petros Drineas (Rensselaer Polytechnic Institute)

#### Randomized algorithms for numerical linear algebra

*Wednesday 30 April 2014 at 13.00, JCMB 4312*

##### Abstract

The introduction of randomization in the design and analysis of algorithms for
matrix computations (such as matrix multiplication, least-squares regression,
the Singular Value Decomposition (SVD), etc.) over the last decade provided a
new paradigm and a complementary perspective to traditional numerical linear
algebra approaches. These novel approaches were motivated by technological
developments in many areas of scientific research that permit the automatic
generation of large data sets, which are often modeled as matrices.

In this talk we will outline how such approaches can be used to approximate
problems ranging from matrix multiplication and the Singular Value
Decomposition (SVD) of matrices to the Column Subset Selection Problem and the
CX decomposition. Application of the proposed algorithms to data analysis
tasks in population genetics will also be discussed.

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