Let $x \in \mathbb{R}^n$ belongs to $S$ where $$ S= \{x \in \mathbb{R}^n \mid x \succ 0, \|x\|_{\infty} \leq M\} $$ where $\succ$ is the generalized inequality which means all elements of $x$ are positive and $\log$ is natural logarithm. Use the following theorem to show that $f(x)=\sum_{i=1}^nx_i\log(x_i)$ is $\frac{1}{M}$-strongly convex over $S$.
Theorem: f is $\alpha$-strongly convex if and only if $\nabla^2f(x) \succeq \alpha I$ for all $x$.
Definition:$f$ is $\alpha$-strongly convex if there exist a constant $\alpha$ such that $$ f(y) \geq f(x)+\left<f '(x),y-x\right>+\frac{\alpha}{2}\|y-x\|^2$$ or $$ \left<f'(y)-f '(x),y-x\right> \geq \alpha\|y-x\|^2$$
for all $x,y$.
First of all, It seems to me that in the definition of $\alpha$-strongly convex function should have a coefficient of $\alpha$ but not $\frac{\alpha}{2}$.
Now here goes the proof $$ \begin{aligned} \frac{\partial^2 f}{\partial x_i \partial_j} & = &\frac{\partial}{\partial x_j}[\log(x_i) + 1] \\ & = & \left \{ \begin{aligned} 1/x_i \quad \text{if } i =j \\ 0 \quad \text{if } i \neq j \end{aligned} \right . \end{aligned} $$
Since $0<x_i\leq M$, then $1/x_i \geq 1/M$
Thus $\nabla^2 f \geq \frac{1}{M} I$, which is the theorem for $1/M$-strongly convex function.