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Adaptive cubic overestimation methods for unconstrained optimization
- Abstract:
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An Adaptive Cubic Overestimation (ACO) algorithm for unconstrained optimization, generalizing a method due to Nesterov & Polyak (Math. Programming 108, 2006, pp 177-205), is proposed. At each iteration of Nesterov & Polyak's approach, the global minimizer of a local cubic overestimator of the objective function is determined, and this ensures a significant improvement in the objective so long as the Hessian of the objective is Lipschitz continuous and its Lipschitz constant is availab...
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Bibliographic Details
- Publisher:
- Unspecified
- Publication date:
- 2007-10-01
Item Description
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uuid:68c5c310-dec1-43aa-a3f2-feaca56d8222
- Local pid:
- oai:eprints.maths.ox.ac.uk:1082
- Deposit date:
- 2011-05-20
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- Copyright date:
- 2007
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