Support vector machine (SVM) is an optimal margin based classification technique in
machine learning. SVM is a binary linear classifier which has been extended to non-linear …

Photoacoustic computed tomography (PACT), also known as optoacoustic tomography, is
an emerging imaging technique that holds great promise for biomedical imaging. PACT is a …

A large number of imaging problems reduce to the optimization of a cost function, with
typical structural properties. The aim of this paper is to describe the state of the art in …

This monograph is about a class of optimization algorithms called proximal algorithms. Much
like Newton's method is a standard tool for solving unconstrained smooth optimization …

In this paper, we propose an inertial forward-backward splitting algorithm to compute a zero
of the sum of two monotone operators, with one of the two operators being co-coercive. The …

We generalize Newton-type methods for minimizing smooth functions to handle a sum of two
convex functions: a smooth function and a nonsmooth function with a simple proximal …

We consider the minimization of a function G defined on R^N, which is the sum of a (not
necessarily convex) differentiable function and a (not necessarily differentiable) convex …

The forward–backward splitting method (FBS) for minimizing a nonsmooth composite
function can be interpreted as a (variable-metric) gradient method over a continuously …

This thoroughly updated new edition presents state of the art sparse and multiscale image
and signal processing. It covers linear multiscale geometric transforms, such as wavelet …

We survey optimization problems that involve the cardinality of variable vectors in
constraints or the objective function. We provide a unified viewpoint on the general problem …