14 citations · 18 across the 4 of their papers we have counts for
5 papers
A Hölderian backtracking method for min-max and min-min problems
Jérôme Bolte, Lilian Glaudin, Edouard Pauwels +1
We present a new algorithm to solve min-max or min-min problems out of the convex world. We use rigidity assumptions, ubiquitous in learning, making our method applicable to many o…
Solving Composite Fixed Point Problems with Block Updates
Patrick L. Combettes, Lilian E. Glaudin
Various strategies are available to construct iteratively a common fixed point of nonexpansive operators by activating only a block of operators at each iteration. In the more chal…
Variable metric algorithms driven by averaged operators
Lilian E. Glaudin
The convergence of a new general variable metric algorithm based on compositions of averaged operators is established. Applications to monotone operator splitting are presented.
Proximal Activation of Smooth Functions in Splitting Algorithms for Convex Image Recovery
Patrick L. Combettes, Lilian E. Glaudin
Structured convex optimization problems typically involve a mix of smooth and nonsmooth functions. The common practice is to activate the smooth functions via their gradient and th…
Quasinonexpansive Iterations on the Affine Hull of Orbits: From Mann's Mean Value Algorithm to Inertial Methods
Patrick L. Combettes, Lilian E. Glaudin
Fixed point iterations play a central role in the design and the analysis of a large number of optimization algorithms. We study a new iterative scheme in which the update is obtai…