Computational Mathematics and Scientific Computing Seminar

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Limited-Memory BFGS with Displacement Aggregation

Speaker: Albert Berahas, Lehigh

Location: Warren Weaver Hall 1302

Date: Nov. 1, 2019, 10 a.m.

Synopsis:

We present a displacement aggregation strategy for the curvature pairs stored in a limited-memory BFGS method such that the resulting (inverse) Hessian approximations are equal to those derived from a full-memory BFGS method. Using said strategy, an algorithm employing the limited-memory method can achieve the same convergence properties as when full-memory Hessian approximations are employed. We illustrate the performance of an LBFGS algorithm that employs the aggregation strategy.