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December 1st, 2010, 03:34 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 ith 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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absolute, constraint, error, minimization, quadratic 
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