The unprecedented growth in data generation has necessitated the adoption of advanced analytical techniques. Support Vector Machine (SVM) is a powerful machine learning tool that has proven invaluable in classifying observations through optimal hyperplane in higher dimensions. Despite their...

Improvements in technology lead to increasing availability of large data sets which makes the need for data reduction and informative subsamples ever more important. In this paper we construct D -optimal subsampling designs for polynomial regression in one covariate for invariant distributions...

Spatial or spatio-temporal data are frequently encountered in many scientific disciplines. One major challenge in modeling these processes is the high dimensionality of such data; that is, the number of observations is usually enormous. The first part of the dissertation proposes an efficient...