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Matrix. f(x) is concave in 𝑆 if Xᴴ is a Negative Semi-Definite Matrix. Since the Hessian of J(w) is Positive Semidefinite, it can be concluded that the function J(w) is convex. Final Comments - This blog post is aimed at proving the convexity of MSE loss function in a Regression setting by