Novel techniques for sparse representation problems

Abstract

This thesis contains material from papers published in the following peer-reviewed conferences and publication drafts under preparation for the publications in the following peer-reviewed journals where I was the first and corresponding author. Chapter 3 is prepared as W.H. Chai, and C. Quek. A novel Quasi-Newton Technique for Composite Convex Minimization. Pattern Recognition (Under revision) The contributions of the co-authors are as follows:  I defined the initial project direction  Assoc Prof Quek edited the manuscript drafts.  The manuscript was revised by Assoc Prof Quek.  I generated the idea, derived the theory, designed the study and the algorithm, performed all the experimental works, and analyzed the results at the School of Computer Science and Rolls-Royce@NTU Corporate Lab. Chapter 4 is prepared as W.H. Chai, and C. Quek. Representation Recovery via -norm Minimization with Corrupted Data. Information Sciences (Submitted)The contributions of the co-authors are as follows: Assoc Prof Quek provided the initial project direction and edited the manuscript drafts. The manuscript was revised by Assoc Prof Quek. I generated the idea, derived the theory, designed the study and the algorithm, performed all the experimental works, and analyzed the results at the School of Computer Science and Rolls-Royce@NTU Corporate Lab.Chapter 5 is prepared as W.H. Chai, and C. Quek. Feature Selection for Dictionary Transfer. Pattern Recognition Letters (Under preparation for publication)The contributions of the co-authors are as follows:x  I defined the initial project direction  Assoc Prof Quek edited the manuscript drafts. The manuscript was revised by Assoc Prof Quek. I generated the idea, derived the theory, designed the study and the algorithm, performed all the experimental works, and analyzed the results at the School of Computer Science and Rolls-Royce@NTU Corporate Lab.