2 citations · 4 across the 9 of their papers we have counts for
13 papers · 1 filter
On the Douglas-Rachford algorithm for solving possibly inconsistent optimization problems
Heinz H. Bauschke, Walaa M. Moursi
More than 40 years ago, Lions and Mercier introduced in a seminal paper the Douglas-Rachford algorithm. Today, this method is well recognized as a classical and highly successful s…
On compositions of special cases of Lipschitz continuous operators
Pontus Giselsson, Walaa M. Moursi
Many iterative optimization algorithms involve compositions of special cases of Lipschitz continuous operators, namely firmly nonexpansive, averaged and nonexpansive operators. The…
On the behaviour of the Douglas-Rachford algorithm for minimizing a convex function subject to a linear constraint
Heinz H. Bauschke, Walaa M. Moursi
The Douglas-Rachford algorithm (DRA) is a powerful optimization method for minimizing the sum of two convex (not necessarily smooth) functions. The vast majority of previous resear…
Differentiating Through a Cone Program
Akshay Agrawal, Shane Barratt, Stephen Boyd +2
We consider the problem of efficiently computing the derivative of the solution map of a convex cone program, when it exists. We do this by implicitly differentiating the residual…
Generalized monotone operators and their averaged resolvents
Heinz H. Bauschke, Walaa M. Moursi, Xianfu Wang
The correspondence between the monotonicity of a (possibly) set-valued operator and the firm nonexpansiveness of its resolvent is a key ingredient in the convergence analysis of ma…
Numerical explorations of feasibility algorithms for finding points in the intersection of finite sets
Heinz H. Bauschke, Sylvain Gretchko, Walaa M. Moursi
Projection methods are popular algorithms for iteratively solving feasibility problems in Euclidean or even Hilbert spaces. They employ (selections of) nearest point mappings to ge…