Electronic Resource
Springer
Journal of optimization theory and applications
104 (2000), S. 539-558
ISSN:
1573-2878
Keywords:
nonsmooth convex optimization
;
Moreau–Yosida regularization
;
strong convexity
;
inexact function and gradient evaluations
;
BFGS method
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract We propose an implementable BFGS method for solving a nonsmooth convex optimization problem by converting the original objective function into a once continuously differentiable function by way of the Moreau–Yosida regularization. The proposed method makes use of approximate function and gradient values of the Moreau-Yosida regularization instead of the corresponding exact values. We prove the global convergence of the proposed method under the assumption of strong convexity of the objective function.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1004633524446
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