Corpus ID: 85556114

Limited-Memory BFGS with Displacement Aggregation.

@article{Berahas2019LimitedMemoryBW,
  title={Limited-Memory BFGS with Displacement Aggregation.},
  author={Albert S. Berahas and Frank E. Curtis and Baoyu Zhou},
  journal={arXiv: Optimization and Control},
  year={2019}
}

Albert S. Berahas, Frank E. Curtis, Baoyu Zhou

Published 2019

Mathematics

arXiv: Optimization and Control

A displacement aggregation strategy is proposed for the curvature pairs stored in a limited-memory BFGS method such that the resulting (inverse) Hessian approximations are equal to those that would be derived from a full-memory BFGS method. This means that, if a sufficiently large number of pairs are stored, then an optimization algorithm employing the limited-memory method can achieve the same theoretical convergence properties as when full-memory (inverse) Hessian approximations are stored… CONTINUE READING

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