Prove that $\,\big\langle\nabla f(x) - \nabla f(y),\, (x-y)\big\rangle \geq m\,\left\lVert x-y\right\rVert^2, \;\,m > 0\,$ for strong convex function $f: \mathbb R^n \to\mathbb R$. Is it true for strictly convex function.
I have to clue to prove above statement. Can anyone give me some hints?
We wish to show that if a differentiable function $f:\mathbb R^n \to \mathbb R$ is strongly convex with parameter $m > 0$ then it is strongly monotone with parameter $m$.
To say that $f$ is strongly convex with parameter $m$ means that the function $h(x) = f(x) - \frac{m}{2} \|x\|^2$ is convex. (At least, that's my favorite definition of strong convexity. It has the advantage of making sense even for nondifferentiable functions.)
Because $h$ is a convex function, it is monotone: \begin{align} &\langle \nabla h(x) - \nabla h(y), x - y \rangle \geq 0 \quad \text{for all } x,y \\ \implies & \langle \nabla f(x)- mx - (\nabla f(y) - my), x - y \rangle \geq 0 \quad \text{for all } x,y \\ \implies & \langle \nabla f(x) - \nabla f(y), x - y \rangle \geq m \| x - y \|^2 \quad \text{for all } x,y. \end{align} Thus $f$ is strongly monotone with parameter $m$.