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 December 1st, 2010, 02:34 AM #1 Newbie   Joined: Dec 2010 Posts: 1 Thanks: 0 least absolute error minimization with quadratic constraint Hello everyone, I have the following optimization problem: Given a set of N points of length=2 (the i-th point is written n_i) , find the point v (of norm 2) such that: maximize the sum_i^N |n_i^T v| with respect to ||v||=2 where n_i^T is the transpose of n_i. In other words, I am looking for the point v that minimizes the sum of least absolute errors. The constraint ||v||=2 is quadratic. Thus, this system could be called least absolute error minimization with a quadratic constraint. Does anyone have a solution for that kind of problems? Benoit

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