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Variational methods - prove f is convex in R->R
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[QUOTE="braindead101, post: 1634048, member: 42860"] Suppose f:R^N -> R is twice differentiable. Prove that f is convex if and only if its Hessian gradiant^2 f(x) is nonnegative. How do I go about proving this? and my professor said I only need to consider when N=1. so R->R. any help would be greatly appreciated. For proving it backwards, this is what i have, but i am not sure if it is correct. If the Hessian of F is nonnegative definite, then the function is locally strictly convex. A function that is locally strictly convex everywhere is strictly convex. and I am not sure how to prove it other way [/QUOTE]
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Variational methods - prove f is convex in R->R
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