Let function $f : \mathbb{R}^n \to \mathbb{R}$ with $\|\cdot\|$ is Euclidean norm then we have the following definitions:
A function $f$ is coercive if $\lim\limits_{\|x\|\rightarrow \infty}f(x) = \infty$.
A function $f$ is convex if for all $x,y\in \mathbb{R}^n$ and $\lambda \in [0;1]$ $$f((1-\lambda)x + \lambda y)\leq (1-\lambda)f(x) + \lambda f(y)$$
A function $f$ is strongly convex if there is exists a constant $\kappa >0$ such that for all $x,y\in\mathbb{R}^n$ and $\lambda \in [0;1]$ $$f((1-\lambda)x + \lambda y) \leq (1-\lambda)f(x) + \lambda f(y)-\dfrac{\kappa}{2} \|x-y\|^2$$
Problem: Prove that if $f$ is strongly convex then $f$ is coercive.
Note: There is another post about this kind of problem but the definition of strongly convex function on that post used a $C^2$ function $f$. I think that the following lemmas maybe useful for completing the proof.
Lemma 1: If $f$ is strongly convex function then $f$ is convex.
Lemma 2: $f$ is strongly convex function with some $\kappa>0$ iff $f - \dfrac{\kappa}{2}\|\cdot\|$ is convex function.