Prerequisites: Minimum grade of C- in MATH240, MATH461, or ENEE290. Software prerequisite- Matlab. Corequisites: ENEE324 or STAT400
Students will be introduced to linear, nonlinear, unconstrained, constrained optimization. Convex optimization will be highlighted. Applications will be considered, in particular in the area of machine learning. Some optimization algorithms may be discussed, time permitting.