Regularization methods are a key tool in the solution of inverse problems. They are used to
introduce prior knowledge and allow a robust approximation of ill-posed (pseudo-) inverses …

We consider online allocation problems with concave revenue functions and resource
constraints, which are central problems in revenue management and online advertising. In …

Correction to: Convex Analysis and Monotone Operator Theory in Hilbert Spaces Page 1
Correction to: Convex Analysis and Monotone Operator Theory in Hilbert Spaces Correction …

The primary aim of this book is to present the conjugate and subdifferential calculus using
the method of perturbation functions in order to obtain the most general results in this field …

Regularization methods aimed at finding stable approximate solutions are a necessary tool
to tackle inverse and ill-posed problems. Inverse problems arise in a large variety of …

We characterize, in the Anscombe–Aumann framework, the preferences for which there are
a utility functionu on outcomes and an ambiguity indexc on the set of probabilities on the …

Like differentiability, convexity is a natural and powerful property of functions that plays a
significant role in many areas of mathematics, both pure and applied. It ties together notions …

BREGMAN DISTANCES, TOTALLY CONVEX FUNCTIONS, AND A METHOD FOR SOLVING
OPERATOR EQUATIONSIN BANACH SPACES Page 1 BREGMAN DISTANCES, TOTALLY …

A broad class of optimization algorithms based on Bregman distances in Banach spaces is
unified around the notion of Bregman monotonicity. A systematic investigation of this notion …

Full article: Two Strong Convergence Theorems for a Proximal Method in Reflexive Banach
Spaces Skip to Main Content Taylor and Francis Online homepage Browse Search Publish …