Semismooth Newton Methods for Variational Inequalities and Constrained Optimization Problems in Function Spaces

By Michael Ulbrich. MOS-SIAM Series on Optimization, 2011

375 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Bilevel Optimization Approach for Parameter Learning in Variational Models (2013, background): “[17, 30] and the references given there and Dmax(0, x) = χ{x≥0} is a generalized or Newton derivative.”
Second Order Optimality Conditions and Their Role in PDE Control (2015, neutral): “We refer to the monograph [85] and the references therein.”
Proper Orthogonal Decomposition for Linear-Quadratic Optimal Control (2013, neutral): “15); see [24, 26, 74].”
NONSMOOTH ANALYSIS AND OPTIMIZATION (2017, methodology): “Finally, a vector-valued function is semismooth if and only if all its component functions are semismooth; see [Ulbrich 2011, Proposition 2.10].”