seniorSVM
Why is SVM optimization considered a convex quadratic programming problem?
Updated May 17, 2026
Short answer
Because the objective is quadratic in weights and constraints are linear.
Deep explanation
The primal SVM objective minimizes ||w||² with linear constraints. This forms a convex quadratic function, ensuring a single global minimum exists. Convexity guarantees stability and predictable optimization behavior.
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