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"The aim of this book is to provide the simplest formulations that can be derived "from first principles" with simple arguments"--
Presents the theory of submodular functions in a self-contained way from a convex analysis perspective, presenting tight links between certain polyhedra, combinatorial optimization and convex optimization problems. In particular, it describes how submodular function minimization is equivalent to solving a variety of convex optimization problems.
Presents optimization tools and techniques dedicated to sparsity-inducing penalties from a general perspective. The book covers proximal methods, block-coordinate descent, working-set and homotopy methods, and non-convex formulations and extensions, and provides a set of experiments to compare algorithms from a computational point of view.
Tilmeld dig nyhedsbrevet og få gode tilbud og inspiration til din næste læsning.
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