Abstract
In the same spirit as the one of the paper (Hiriart-Urruty and Malick in J. Optim. Theory Appl. 153(3):551–577, 2012) on positive semidefinite matrices, we survey several useful properties of the rank function (of a matrix) and add some new ones. Since the so-called rank minimization problems are the subject of intense studies, we adopt the viewpoint of variational analysis, that is the one considering all the properties useful for optimizing, approximating or regularizing the rank function.
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Notes
D “pseudo-diagonal” means that d ij =0 for \(i\not=j\). One also uses the notation \(\operatorname{diag}_{m,n}[\sigma_{1},\dots,\sigma_{p}]\) for D.
The notation for the SVD is a bit nonstandard. Usually, a singular value decomposition takes the form UΣV T (i.e., V T instead of V). But there is no difference from the mathematical point of view.
A nonempty closed set S is an Euclidean space E is called prox-regular at a point \(\overline{x}\in S\) if the projection set P S (x) of x on S is single-valued around \(\overline{x}\).
Such a phenomenon happens because the objective function is not continuous. Indeed, if \(\mathcal {C}\) is a connected set, if \(f:\mathcal{C} \longrightarrow\mathbb{R}\) is a continuous function, and if every point in \(\mathcal{C}\) is a local minimizer or a local maximizer of f, then f is necessarily constant on \(\mathcal{C}\) (see Behrends et al. 2007).
The convex hull or convex envelope of a function f is the largest possible convex function below f. Its epigraph (i.e., what is above the graph) is exactly the convex hull of the epigraph of f (see Hiriart-Urruty and Lemaréchal 1993).
J.-J. Moreau presented this approximation process as an example of inf-convolution or epigraphic addition of two functions; it was in 1962, exactly 50 years ago. This date marks the birth of modern convex analysis and optimization.
D. Drusvyatskiy, personal communication (August 2012).
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Acknowledgements
We thank the various readers or referees who, after the first circulation of this survey paper (July 2012), provided comments, improvements and additional references.
Last but not least, we would like to thank Professor M. Goberna (University of Alicante) for his instrumental role in the publication of this survey paper.
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Hiriart-Urruty, JB., Le, H.Y. A variational approach of the rank function. TOP 21, 207–240 (2013). https://doi.org/10.1007/s11750-013-0283-y
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DOI: https://doi.org/10.1007/s11750-013-0283-y
Keywords
- Rank of matrix
- Optimization
- Nonsmooth analysis
- Moreau–Yosida regularization
- Generalized subdifferentials