183 citations · 706 across the 60 of their papers we have counts for
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stat.ML2019★ 2 cited
Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling
Nicholas Sterge, Bharath Sriperumbudur, Lorenzo Rosasco +1
In this paper, we propose and study a Nyström based approach to efficient large scale kernel principal component analysis (PCA). The latter is a natural nonlinear extension of clas…
stat.ML2019★ 3 cited
Efficient online learning with kernels for adversarial large scale problems
Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
We are interested in a framework of online learning with kernels for low-dimensional but large-scale and potentially adversarial datasets. We study the computational and theoretica…