Solves a convex optimization problem with a linear objective minimize f0(x) subject to fk(x) <= 0, k = 1, ..., mnl G*x <= h A*x = b. f is vector valued, convex and twice differentiable. The linear inequalities are with respect to a cone C defined as the Cartesian product of N + M + 1 con
(F ConvexProg, G, h, A, b *matrix.FloatMatrix, dims *sets.DimensionSet, solopts *SolverOptions)
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