EECS 260

Optimization

University of California, Merced · UGRD · Fall 2026

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Introduction of theory and numerical methods for continuous multivariate optimization (unconstrained and constrained), including: line-search and trust-region strategies; conjugate-gradient, Newton, quasi-Newton and large-scale methods; linear programming; quadratic programming; penalty and augmented Lagrangian methods; sequential quadratic programming; and interior-point methods.

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Class #california_merced-0780Fall 2026UGRD4 credits
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