Semismooth Newton and quasi-Newton methods in weighted ℓ1-regularization.

We investigate semismooth Newton and quasi-Newton methods for minimization problems arising from weighted ℓ1-regularization. We give proofs of the local convergence of these methods and show how their interpretation as active set methods leads to the development of efficient numerical implementations of these algorithms. We also propose and analyze Broyden updates for the semismooth quasi-Newton method. The efficiency of these methods is analyzed and compared with standard implementations. The paper concludes with some numerical examples that include both linear and nonlinear operator equations. [ABSTRACT FROM AUTHOR]