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Fast Approximate L_infty Minimization: Speeding Up Robust Regression
[article]
2013
arXiv
pre-print
Minimization of the L_∞ norm, which can be viewed as approximately solving the non-convex least median estimation problem, is a powerful method for outlier removal and hence robust regression. However, current techniques for solving the problem at the heart of L_∞ norm minimization are slow, and therefore cannot scale to large problems. A new method for the minimization of the L_∞ norm is presented here, which provides a speedup of multiple orders of magnitude for data with high dimension. This
arXiv:1304.1250v1
fatcat:fck5c6zao5dxfeq3ixnpz3wtly