##### Department of Mathematics,

University of California San Diego

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### Center for Computational Mathematics Seminar

## Jeb Runnoe

#### UCSD

## Recent Developments in Quasi-Newton Methods for Numerical Optimization

##### Abstract:

Quasi-Newton methods form the basis of many effective methods for unconstrained and constrained optimization. Quasi-Newton methods require only the first-derivatives of the problem to be provided and update an estimate of the Hessian matrix of second derivatives to reflect new approximate curvature information found during each iteration. In the years following the publication of the Davidon-Fletcher-Powell (DFP) method in 1963 the Broyden-Fletcher-Goldfarb-Shan

### May 17, 2022

### 11:00 AM

Zoom ID 954 6624 3503

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