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ICPR
2008
IEEE
9 years 8 months ago
Solving quadratically constrained geometrical problems using lagrangian duality
In this paper we consider the problem of solving different pose and registration problems under rotational constraints. Traditionally, methods such as the iterative closest point ...
Carl Olsson, Anders Eriksson
JGO
2008
111views more  JGO 2008»
8 years 7 months ago
A geometric framework for nonconvex optimization duality using augmented lagrangian functions
We provide a unifying geometric framework for the analysis of general classes of duality schemes and penalty methods for nonconvex constrained optimization problems. We present a ...
Angelia Nedic, Asuman E. Ozdaglar
ACCV
2007
Springer
8 years 11 months ago
Efficiently Solving the Fractional Trust Region Problem
Normalized Cuts has successfully been applied to a wide range of tasks in computer vision, it is indisputably one of the most popular segmentation algorithms in use today. A number...
Anders P. Eriksson, Carl Olsson, Fredrik Kahl
SIAMJO
2002
133views more  SIAMJO 2002»
8 years 7 months ago
SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
Abstract. Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective...
Philip E. Gill, Walter Murray, Michael A. Saunders
OL
2011
332views Neural Networks» more  OL 2011»
8 years 2 months ago
A robust implementation of a sequential quadratic programming algorithm with successive error restoration
We consider sequential quadratic programming (SQP) methods for solving constrained nonlinear programming problems. It is generally believed that SQP methods are sensitive to the a...
Klaus Schittkowski
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