8 citations · 26 across the 13 of their papers we have counts for
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stat.ML2016
Kernel regression, minimax rates and effective dimensionality: beyond the regular case
Gilles Blanchard, Nicole Mücke
We investigate if kernel regularization methods can achieve minimax convergence rates over a source condition regularity assumption for the target function. These questions have be…
math.ST2016★ 8 cited
Parallelizing Spectral Algorithms for Kernel Learning
Gilles Blanchard, Nicole Mücke
We consider a distributed learning approach in supervised learning for a large class of spectral regularization methods in an RKHS framework. The data set of size n is partitioned…