Dr. rer. nat.

Nicole Mücke

Institut für Stochastik und Anwendungen
Lehrstuhl für Stochastik


+49 711 685-65353


Pfaffenwaldring 57
70569 Stuttgart
Room: 8.554

Office Hours

nach Vereinbarung

[1] Gilles Blanchard, Nicole Mücke, Optimal Rates for Regularization of Statistical Inverse Learning Problems, Foundations of Computational Mathematics (2017) 

[2] Nicole Mücke, Gilles Blanchard, Parallelizing Spectrally Regularized Kernel Algorithms,
Journal of Machine Learning Research (2018)



[3] Nicole Mücke, LocalNysation: A bottom up approach to efficient localized kernel regression, accepted for publication and poster presentation for AISTATS 2019
arXiv: 1707.03220 (2017)

[4] Nicole Mücke, Adaptivity for Regularized Kernel Methods by Lepskii's Principle,
arXiv:1804.05433v1 (2018)

[5] Gilles Blanchard, Nicole Mücke, Kernel regression, minimax rates and effective dimensionality: beyond the regular case, arXiv:1611.03979v1 (2016)

[6] Nicole Mücke, Gergely Neu, Lorenzo Rosasco, Beating SGD Saturation with Tail-Averaging and Minibatching, arxiv.org/abs/1902.08668 (2019)



Statistical Machine Learning, Efficiency of Kernel Methods, Adaptivity, Inverse Learning Problems

Please follow the link to the SWSL-Workshop, 9th-11th July 2019


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