I need help. In my class we're not using Hessian matrices with our convex optimization. I don't really understand how to find out if it's concave or convex. All the videos I look at and articles I read pretty much only use Hessian Matrices and what not.
I don't really understand this Convex Theorem either.
f(λx+(1−λ)y)≥λf(x)+(1−λ)f(y) f(λx+(1−λ)y)≤λf(x)+(1−λ)f(y) It seems like it's saying the function should be larger than the extrema for concavity and less than for convexity?
I get what concave and convex mean, I looked at a fantastic video that explained where they derived that Convex theorem equation, and I get that you should use the second derivative. But I don't really understand how you find out or use the second derivative.
I'm terribly sorry. Calculus was several years ago. Do you think someone could please help me out? I know this has to be a very annoying and simple question for you guys...