On the Complexity of Steepest Descent, Newton's and Regularized Newton's Methods for Nonconvex Unconstrained Optimization Problems.
It is shown that the steepest-descent and Newton's methods for unconstrained nonconvex optimization under standard assumptions may both require a number of iterations and function evaluations arbitrarily close to O(ε ?2) to drive the norm of the gradient below ε. This shows that the upper bound...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2010
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