Let $f:\mathbb{R} \rightarrow \mathbb{R}$ be a continuous, differentiable function. Is there a known algorithm that fits $f$ with $g$, which is an order-$n$ polynomial that is convex, in the least square sense?
Approximating a function with a convex function
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linear-algebra
optimization
convex-optimization
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0Yes. It would be more interesting if the supports of $f$ and $g$ are bounded intervals. – 2012-12-31
1 Answers
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I don't think so. For any convex function $g$, $\|\sin x-g(x)\|_{l_2} = \infty$. Similarly I'm not sure how you would want to fit a convex function to $f(x)=-x^2$.
Locally you can always approximate a function by its convex truncated Taylor series $f(x_0 + y) \approx f(x_0) + y f'(x_0) + \frac{1}{2}y^2 f''(x_0)$ provided that $f''(x_0)>0$. The same can be done in higher dimensions at points where the Hessian of $f$ is positive-definite.