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Center for Nonlinear Studies |
In this talk I will present methods of Topological Data Analysis (TDA) applied to data science. TDA is mathematically rigorous way of building simplified models of data that is stable with respect to noise. I will present models that can be used to compare datasets by using various standard classification methods as well as methods that represent layout of high dimensional and complicated data suitable for exploratory data analysis. I will show how TDA can be applied to various point clouds equipped with distance or similarity measures as well as time series.
Host: Information Science and Technology Institute (ISTI)