Machine learning, Balance cut and Total variation

Start: 02/06/2013 - 12:30pm
End  : 02/06/2013 - 1:30pm

Applied Math Seminar

Thomas Boris Laurent (UC Riverside)


Machine Learning is the branch of Artificial Intelligence which is devoted to the design and study of algorithms that learn patterns from large data sets in order to make intelligent decisions. In this talk we will be concerned with the problem of partitioning a large and high dimensional data set into groups of data having ``similar behavior''. One successful approach is to construct a graph from the data and then to cut this graph in a sensible way. Here we will present a fast algorithm, based of total variation optimization technique recently developed in image processing, that accomplish this task.

CGU, South math building

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