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A second-order Taylor polynomial computed from gradient and Hessian data
Statement
For , the second-order Taylor polynomial at the origin is .
Facts & Assumptions
Given: .
The second-order Taylor polynomial is determined by the value, gradient, and Hessian (Second-order Taylor expansion ).
The standard algebra rules compute the displayed derivatives (Sums, scalar multiples, products and quotients: , , , and when ).
Proof
At , , , and .
Substitution into [L1] gives , namely the claimed polynomial.
Thus the computed value, gradient, and Hessian yield the stated second-order approximation.
Depends on
- Second-order Taylor expansion $f(a+h)=f(a)+\nabla f(a)\cdot h+\tfrac12h^TH_f(a)h+o(\|h\|^2)$
- Sums, scalar multiples, products and quotients: $(f+g)'(c) = f'(c) + g'(c)$, $(\alpha f)'(c) = \alpha f'(c)$, $(fg)'(c) = f'(c)g(c) + f(c)g'(c)$, and $(f/g)'(c) = \bigl(f'(c)g(c) - f(c)g'(c)\bigr)/g(c)^{2}$ when $g(c) \ne 0$
Used by
Nothing in the library uses this result yet.
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 59 results over 15 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- Taylor's theorem in several variables (standard reference, not scraped)