# Material Detail ## Lecture 17: Newton's Method (Cont.)

This video was recorded at Stanford Engineering Everywhere EE364A - Convex Optimization I. Well today, we'll finish up Newton's method, probably won't take up much of the day though. But – then, we'll move on to our absolute last topic, which is Interior Point Methods for Inequality Constraint Problems. So we're studying methods, Newton's method, for solving the following problem. You want to minimize f of x, which is smooth, subject to a x = b. So we're assuming here that a x = b is feasible. I mean, otherwise, the problem is, the whole problem is infeasible; and that we have a starting point x zero that satisfies a x zero = b. So we assume we have a feasible point. ... See the whole transcript at Convex Optimization I - Lecture 17
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