[<<][math][>>][..]Tue Nov 4 22:02:38 EST 2014
Basic idea: - 1-D minimum is easy - compute 1-D minimum across n orthogonal directions - here orthogonal is actually conjugate = orthogonal in metric (ellipsoid) defined by convex optimization Formulated as convex optimization problem -> this is why it only works with symmetric, positive definite matrices.
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