Additive Sparse Grid Fitting

نویسنده

  • Markus Hegland
چکیده

We propose an iterative algorithm for high-dimensional sparse grid regression with penalty. The algorithm is of additive Schwarz type and is thus parallel. We show that the convergence of the algorithm is better than additive Schwarz and examples demonstrate that convergence is between that of additive Schwarz and multiplicative Schwarz procedures. Similarly, the method shows improved performance compared to (additive) iterative methods based on the combination technique. §

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تاریخ انتشار 2002