2 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ML2021★ 1 cited
Statistical Optimality and Computational Efficiency of Nyström Kernel PCA
Nicholas Sterge, Bharath Sriperumbudur
Kernel methods provide an elegant framework for developing nonlinear learning algorithms from simple linear methods. Though these methods have superior empirical performance in sev…
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…