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Directors:
Randolph E. Bank
Philip E. Gill
Michael Holst

Administrative Contact:
Juan Rodriguez

Office: AP&M 7409
Phone: (858)534-9056
Fax: (858)534-5273
E-mail: jcr009@ucsd.edu
Adaptive Cubic Regularization Methods for Nonconvex Unconstrained Optimization

Ziyan Zhu
UCSD

Abstract:

Adaptive cubic regularization methods have several favorable properties for nonconvex optimization. In particular, under mild assumptions, they are globally convergent to a second-order stationary point. In this talk, I will introduce an adaptive cubic regularization method for unconstrained optimization. Methods analogous to those used to solve the trust-region subproblem will be discussed for solving the local cubic model. Some numerical results will be presented that compare a cubic regularized Newton's method, a standard trust-region method and a trust-search method.

Tuesday, November 12, 2019
11:00AM AP&M 2402