The main theme is to show how methods and theory for nonlinear optimization can be developed concisely from the linear case, using only techniques from the calculus of many variables, primarily the Taylor Series Expansion, the Chain Rule and the Inverse Function Theorem. Some familiarity with the general solution of Ax=b, when A is mxn with m < n is desirable, plus some grasp of elementary concepts of vector spaces.
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