The thesis contains all four chapters of my Ph.D. research on deep learning and text mining. The first chapter, "Temporal Topic Analysis with Endogenous and Exogenous Processes'', proposes a topic model which mines temporal economy-related documents with an exogenous economic indicator, and finds the relationship between document topics and the...
In this dissertation, we start with the dictionary learning (DL) based single-frame super-resolution (SR) problem, where low resolution (LR) input frames are super-resolved to high resolution (HR) output frames. We propose to extend the previous single-frame SR methods to multiple-frames, i.e., estimating single HR output frame by multiple LR input...
The goal of this thesis is to design practical algorithms for nonlinear optimization in the case when the objective function is stochastic or nonsmooth. The thesis is divided into three chapters. Chapter 1 describes an active-set method for the minimization of an objective function that is structurally nonsmooth, viz., it...