Dual Smoothing and Value Function Techniques for Variational Matrix Decomposition

This chapter reviews some recent techniques in convex optimization and contributes several novel results. We apply these techniques to the robust principal component analysis (RPCA) problem. A distinguishing feature of this chapter, in the context of this handbook, is the emphasis on a range of optimization formulations of the RPCA problem.