Departmental Colloquium
Roshan Joseph
Georgia Tech
Support Points: An Optimal and Model-Free Method for Subsampling Big Data
Abstract: This talk presents a novel method called support points, which can be used for optimal and model-free subsampling of big data. This method has important applications to many practical problems in statistics and machine learning, particularly when the available data is plentiful and high-dimensional, but the processing of such data is expensive due to computation or storage costs. We also propose an extension of the method called Projected Support Points to deal with high dimensional data, which ensures that the data is well-reduced on low-dimensional projections of the data space.
Note the unusual time.
Friday November 22, 2019 at 1:30 PM in 636 SEO