# Local convergence

## Papers overview

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Highly Cited

2012

Highly Cited

2012

- SIAM J. Matrix Analysis Applications
- 2012

A local convergence theorem for calculating canonical low-rank tensor approximations (PARAFAC, CANDECOMP) by the alternatingâ€¦Â (More)

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Highly Cited

2009

Highly Cited

2009

- NIPS
- 2009

The concave-convex procedure (CCCP) is a majorization-minimization algorithm that solves d.c. (difference of convex functionsâ€¦Â (More)

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2007

2007

- IEEE Congress on Evolutionary Computation
- 2007

Traditionally Evolutionary Algorithms (EAs) choose candidate solutions based on their individual fitnesses, usually withoutâ€¦Â (More)

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Highly Cited

2006

Highly Cited

2006

- SIAM Journal on Optimization
- 2006

Recently, nonlinear programming solvers have been used to solve a range of mathematical programs with equilibrium constraintsâ€¦Â (More)

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Highly Cited

2005

Highly Cited

2005

- SIAM Journal on Optimization
- 2005

A line search method is proposed for nonlinear programming using Fletcher and Leyfferâ€™s filter method, which replaces theâ€¦Â (More)

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Highly Cited

2004

Highly Cited

2004

- 2004

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.orgâ€¦Â (More)

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Highly Cited

2003

Highly Cited

2003

- SIAM Journal on Optimization
- 2003

We examine the local convergence properties of pattern search methods, complementing the previously established globalâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

- 2002

We consider the problem of finding a solution of a constrained (and not necessarily square) system of equations, i.e., weâ€¦Â (More)

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Highly Cited

1998

Highly Cited

1998

- Math. Program.
- 1998

An example of SDPs (semide nite programs) exhibits a substantial di culty in proving the superlinear convergence of a directâ€¦Â (More)

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Highly Cited

1997

Highly Cited

1997

- SIAM Journal on Optimization
- 1997

We introduce an abstract deenition of pattern search methods for solving nonlinear unconstrained optimization problems. Ourâ€¦Â (More)

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