The $\mathcal U$-Lagrangian of a convex function
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- by Claude Lemaréchal, François Oustry and Claudia Sagastizábal
- Trans. Amer. Math. Soc. 352 (2000), 711-729
- DOI: https://doi.org/10.1090/S0002-9947-99-02243-6
- Published electronically: September 21, 1999
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Abstract:
At a given point $\bar {p}$, a convex function $f$ is differentiable in a certain subspace $\mathcal {U}$ (the subspace along which $\partial f(\bar {p})$ has 0-breadth). This property opens the way to defining a suitably restricted second derivative of $f$ at $\bar {p}$. We do this via an intermediate function, convex on $\mathcal {U}$. We call this function the $\mathcal {U}$-Lagrangian; it coincides with the ordinary Lagrangian in composite cases: exact penalty, semidefinite programming. Also, we use this new theory to design a conceptual pattern for superlinearly convergent minimization algorithms. Finally, we establish a connection with the Moreau-Yosida regularization.References
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Bibliographic Information
- Claude Lemaréchal
- Affiliation: INRIA, 655 avenue de l’Europe, 38330 Montbonnot, France
- Email: Claude.Lemarechal@inria.fr
- François Oustry
- Affiliation: INRIA, 655 avenue de l’Europe, 38330 Montbonnot, France
- Email: Francois.Oustry@inria.fr
- Claudia Sagastizábal
- Affiliation: INRIA, BP 105, 78153 Le Chesnay, France
- Email: Claudia.Sagastizabal@inria.fr
- Received by editor(s): July 18, 1996
- Received by editor(s) in revised form: August 1, 1997
- Published electronically: September 21, 1999
- © Copyright 1999 American Mathematical Society
- Journal: Trans. Amer. Math. Soc. 352 (2000), 711-729
- MSC (1991): Primary 49J52, 58C20; Secondary 49Q12, 65K10
- DOI: https://doi.org/10.1090/S0002-9947-99-02243-6
- MathSciNet review: 1487623