Convex analysis is the branch of mathematics devoted to the study of properties of convex functions and convex sets, often with applications in… (More)

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Highly Cited

2009

Highly Cited

2009

- Tsung-Han Chan, Chong-Yung Chi, Yu-Min Huang, Wing-Kin Ma
- 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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2008

Highly Cited

2008

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Highly Cited

2008

Highly Cited

2008

- Pham Dinh Tao
- 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

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

- Andrzej Ruszczynski, Alexander Shapiro
- 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

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

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

- Jun Zhang
- 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

- Kazuo Murota
- 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

- Jan de Leeuw
- 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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