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Learning with Submodular Functions

- A Convex Optimization Perspective

af Francis Bach

indgår i Foundations and Trends (R) in Machine Learning serien

Learning with Submodular Functions af Francis Bach
Bag om Learning with Submodular Functions

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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781601987563
  • Indbinding:
  • Paperback
  • Sideantal:
  • 258
  • Udgivet:
  • 4. December 2013
  • Størrelse:
  • 234x156x14 mm.
  • Vægt:
  • 390 g.
  • 2-3 uger.
  • 9. Oktober 2024

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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.

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