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:minimize <math>\ c^T x \ </math> subject to
: <math>P(a_i^T(x) \
where the parameters <math>a_i \ </math> are independent Gaussian random vectors with mean <math>\bar{a}_i</math> and covariance <math>\Sigma_i \ </math> and <math>p\geq0.5</math>. This problem can be expressed as the SOCP
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:minimize <math>\ c^T x \ </math> subject to
: <math>\bar{a}_i^T (x) + \Phi^{-1}(1-p) \lVert \Sigma_i^{1/2} x \rVert_2 \
where <math>\Phi^{-1} \ </math> is the inverse [[error function]].
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