Identifying Active Manifolds

Authors

  • Warren L. Hare IRMACS, Simon Fraser University
  • Adrian S. Lewis Cornell

Keywords:

Nonsmooth Optimization, Nonconvex Optimization, Active Constraint Identification, Prox-regular, Partly Smooth

Abstract

Determining the "active manifold'' for a minimization problem is a large step towards solving the problem. Many researchers have studied under what conditions certain algorithms identify active manifolds in a finite number of iterations. In this work we outline a unifying framework encompassing many earlier results on identification via the Subgradient (Gradient) Projection Method, Newton-like Methods, and the Proximal Point Algorithm. This framework, prox-regular partial smoothness, has the advantage of not requiring convexity for its conclusions, and therefore extends many of these earlier results.

Author Biographies

Warren L. Hare, IRMACS, Simon Fraser University

Adjunct Professor

Adrian S. Lewis, Cornell

Full Professor

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Published

2007-09-02

How to Cite

Hare, W. L., & Lewis, A. S. (2007). Identifying Active Manifolds. Algorithmic Operations Research, 2(2), 75. Retrieved from https://journals.lib.unb.ca/index.php/AOR/article/view/2793

Issue

Vol. 2 No. 2 (2007)

Section

Articles

License

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