A Trust Region Method for Nonsmooth Convex Optimization

@inproceedings{Sagara2005ATR,
  title={A Trust Region Method for Nonsmooth Convex Optimization},
  author={Nobuko Sagara and Masao Fukushima},
  year={2005}
}
We propose an iterative method that solves a nonsmooth convex optimization problem by converting the original objective function to a once continuously differentiable function by way of Moreau-Yosida regularization. The proposed method makes use of approximate function and gradient values of the MoreauYosida regularization instead of the corresponding exact values. Under this setting, Fukushima and Qi (1996) and Rauf and Fukushima (2000) proposed a proximal Newton method and a proximal BFGS… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 17 references

A globally convergent BFGS method for nonsmooth convex optimization

  • A. I. Rauf, M. Fukushima
  • Journal of Optimization Theory and Applications…
  • 2000
Highly Influential
10 Excerpts

Convex Analysis and Minimization Algorithms

  • J.-B. Hiriart-Urruty, C. Lemaréchal
  • 1993
Highly Influential
3 Excerpts

Optimization Toolbox User ’ s Guide ( Version 2 )

  • R. Mifflin
  • 2000

Trust-Region Methods

  • A. R. Conn, N.I.M. Gould, Ph.L. Toint
  • 2000
1 Excerpt

Numerical Optimization. Springer A TRUST REGION METHOD FOR NONSMOOTH CONVEX OPTIMIZATION

  • J. Nocedal, S. J. Wright
  • 1999
1 Excerpt

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