Randomized Extended Kaczmarz for Solving Least-Squares

نویسندگان

  • Anastasios Zouzias
  • Nikolaos M. Freris
چکیده

We present a randomized iterative algorithm that exponentially converges in expectation to the minimum Euclidean norm least squares solution of a given linear system of equations. The expected number of arithmetic operations required to obtain an estimate of given accuracy is proportional to the square condition number of the system multiplied by the number of non-zeros entries of the input matrix. The proposed algorithm is an extension of the randomized Kaczmarz method that was analyzed by Strohmer and Vershynin.

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عنوان ژورنال:
  • SIAM J. Matrix Analysis Applications

دوره 34  شماره 

صفحات  -

تاریخ انتشار 2013