BFGS with Update Skipping and Varying Memory
BFGS with Update Skipping and Varying Memory
Loading...
Files
Publication or External Link
Date
Advisor
Citation
DRUM DOI
Abstract
We give conditions under which limited-memory quasi-Newton methods with exact line searches will terminate in $n$ steps when minimizing $n$-dimensional quadratic functions. We show that although all Broyden family methods terminate in $n$ steps in their full-memory versions, only BFGS does so with limited-memory. Additionally, we show that full-memory Broyden family methods with exact line searches terminate in at most $n+p$ steps when $p$ matrix updates are skipped. We introduce new limited-memory BFGS variants and test them on nonquadratic minimization problems. (Also cross-referenced as UMIACS-TR-96-49)