# Strong conical hull intersection property, bounded linear regularity, Jameson’s property (G), and error bounds in convex optimization

@article{Bauschke1999StrongCH, title={Strong conical hull intersection property, bounded linear regularity, Jameson’s property (G), and error bounds in convex optimization}, author={Heinz H. Bauschke and J. Borwein and Wu Li}, journal={Mathematical Programming}, year={1999}, volume={86}, pages={135-160} }

Abstract.The strong conical hull intersection property and bounded linear regularity are properties of a collection of finitely many closed convex intersecting sets in Euclidean space. These fundamental notions occur in various branches of convex optimization (constrained approximation, convex feasibility problems, linear inequalities, for instance). It is shown that the standard constraint qualification from convex analysis implies bounded linear regularity, which in turn yields the strong… Expand

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- 2006

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- Math. Program.
- 2006

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#### References

SHOWING 1-10 OF 48 REFERENCES

A Unified Analysis of Hoffman's Bound via Fenchel Duality

- Mathematics, Computer Science
- SIAM J. Optim.
- 1996

Abadie's Constraint Qualification, Metric Regularity, and Error Bounds for Differentiable Convex Inequalities

- Mathematics, Computer Science
- SIAM J. Optim.
- 1997

Constrained best approximation in Hilbert space III. Applications ton-convex functions

- Mathematics
- 1996

Asymptotic constraint qualifications and global error bounds for convex inequalities

- Mathematics, Computer Science
- Math. Program.
- 1999