Convex analysis
Papers overview
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Highly Cited
2009
Highly Cited
2009
- IEEE Transactions on Signal Processing
- 2009
Hyperspectral unmixing aims at identifying the hidden spectral signatures (or endmembers) and their corresponding proportions (or… (More)
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Highly Cited
2008
Highly Cited
2008
Highly Cited
2008
- 2008
This paper is devoted to a thorough study on convex analysis approach to d.c. (difference of convex functions) programming and… (More)
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Highly Cited
2007
Highly Cited
2007
- 2007
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org… (More)
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Highly Cited
2006
Highly Cited
2006
- Math. Oper. Res.
- 2006
We consider optimization problems involving convex risk functions. By employing techniques of convex analysis and optimization… (More)
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2005
2005
- 2005
In his ‘23’ “Mathematische Probleme” lecture to the Paris International Congress in 1900, David Hilbert wrote “Besides it is an… (More)
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Highly Cited
2004
Highly Cited
2004
- 2004
Convex programming is a subclass of nonlinear programming (NLP) that unifies and generalizes least squares (LS), linear… (More)
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Highly Cited
2004
Highly Cited
2004
- Neural Computation
- 2004
From a smooth, strictly convex function phi: Rn --> R, a parametric family of divergence function Dphi(alpha) may be introduced… (More)
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Highly Cited
1998
Highly Cited
1998
- Math. Program.
- 1998
Discrete convex analysis [18, 40, 43, 47] aims to establish a general theoretical framework for solvable discrete optimization… (More)
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Highly Cited
1977
Highly Cited
1977
- 1977
A. In this paper we discuss the convergence of an algorithm for metric and nonmetric multidimensional scaling that is very… (More)
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