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Optimization with convex constraints and convex objectives; notions related to convex optimization such as sub-gradients, normal cones, separating hyperplanes

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Approximate local minima for sum of inverse trigonometric functions

Let $\{a_1, a_2, ..., a_N\} \in [0, 1[^N$, I would like to approximate the minimum of the function $$f(x) = x \sum_{i=1}^N \left(\sin(x)^2 - \sin(a_i x)^2 \right)^{-2} $$ in the domain $x \in {]0, \fr …
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