Principles of nonlinear continuous optimization, that is, minimizing an
objective function that depends nonlinear and continuously on unknown
variables that satisfy constraints. Convex optimization will be
introduced. Applications to data-mining and machine learning ("data
science") will also be introduced.
The Mathematics of Nonlinear Programming, (Undergraduate Texts in
Mathematics)
Anthony L. Peressini, Francis E. Sullivan, J.J. Jr. Uhl
Published by Springer (1993-06-17).
Prerequisites:
One of CO 250, 352, 255) and MATH 128 with a grade of at least 70% or
MATH 138 or 148.
(Not open to General Mathematics students)