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Dimensionality Reduction using Elastic Measures
With the recent surge in big data analytics for hyper-dimensional data there is a renewed interest in dimensionality reduction techniques for machine learning applications.
Spatio-temporal extreme event modeling of terror insurgencies
We show that our model is able to predict the intensity of future attacks for 2019-2021 while considering various covariates of interest such as population density, number of regional languages spoken, and the density of population supporting the opposing government.
Generative Models for Functional Data using Phase and Amplitude Separation
This paper presents an approach that relies on separating the phase (x-axis) and amplitude (y-axis), then modeling these components using joint distributions.
Computation Statistics Theory Statistics Theory 62F99
