Low Complexity Regularization of Inverse Problems
Low Complexity Regularization of Inverse Problems
This thesis is concerned with recovery guarantees and sensitivity analysis of variational regularization for noisy linear inverse problems. This is cast as aconvex optimization problem by combining a data fidelity and a regularizing functional promoting solutions conforming to some notion of low complexity related to their non-Smoothness points. Our approach, …