Forward–backward and Douglas–Rachford splitting are methods for structured nonsmooth optimization. With the aim to use smooth optimization techniques for nonsmooth problems, the forward–backward and Douglas–Rachford envelopes where recently proposed. Under specific problem assumptions, these envelope functions have favorable smoothness and convexity properties and their stationary points coincide with the fixed-points of the underlying algorithm operators. This allows for solving such nonsmooth optimization problems by minimizing the corresponding smooth convex envelope function. In this paper, we present a general envelope function that unifies and generalizes existing ones. We provide properties of the general envelope function that sharp...
In this thesis, we develop and investigate numerical methods for solving nonsmooth convex optimizati...
For constrained nonsmooth optimization problems, continuously differentiable penalty functions and b...
The class of majorization–minimization algorithms is based on the principle of successively minimizi...
Nonsmooth optimization problems arise in an ever-growing number of applications in science and engin...
Nonsmooth optimization problems arise in an ever-growing number of applications in science and engi...
Nonsmooth optimization problems arise in an ever-growing number of applications in science and engin...
In this paper we propose a new approach for constructing efficient schemes for nonsmooth convex opti...
© 2017, Springer Science+Business Media New York. The forward–backward splitting method (FBS) for mi...
© 2014 IEEE. We propose a new approach for analyzing convergence of the Douglas-Rachford splitting m...
We adapt the Douglas–Rachford (DR) splitting method to solve nonconvex feasibility problems by study...
We propose a new approach for analyzing convergence of the Douglas-Rachford splitting method for sol...
We propose a new approach for analyzing convergence of the Douglas-Rachford splitting method for sol...
December 19, 1999 (Revised) At least three different "envelope theorems" have proved useful for econ...
AbstractIn envelope-constrained filtering, the filter is optimized subject to the constraint that th...
We study the applicability of the Peaceman–Rachford (PR) splitting method for solving nonconvex opti...
In this thesis, we develop and investigate numerical methods for solving nonsmooth convex optimizati...
For constrained nonsmooth optimization problems, continuously differentiable penalty functions and b...
The class of majorization–minimization algorithms is based on the principle of successively minimizi...
Nonsmooth optimization problems arise in an ever-growing number of applications in science and engin...
Nonsmooth optimization problems arise in an ever-growing number of applications in science and engi...
Nonsmooth optimization problems arise in an ever-growing number of applications in science and engin...
In this paper we propose a new approach for constructing efficient schemes for nonsmooth convex opti...
© 2017, Springer Science+Business Media New York. The forward–backward splitting method (FBS) for mi...
© 2014 IEEE. We propose a new approach for analyzing convergence of the Douglas-Rachford splitting m...
We adapt the Douglas–Rachford (DR) splitting method to solve nonconvex feasibility problems by study...
We propose a new approach for analyzing convergence of the Douglas-Rachford splitting method for sol...
We propose a new approach for analyzing convergence of the Douglas-Rachford splitting method for sol...
December 19, 1999 (Revised) At least three different "envelope theorems" have proved useful for econ...
AbstractIn envelope-constrained filtering, the filter is optimized subject to the constraint that th...
We study the applicability of the Peaceman–Rachford (PR) splitting method for solving nonconvex opti...
In this thesis, we develop and investigate numerical methods for solving nonsmooth convex optimizati...
For constrained nonsmooth optimization problems, continuously differentiable penalty functions and b...
The class of majorization–minimization algorithms is based on the principle of successively minimizi...