Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering

no code implementations • 15 May 2019 • Manuel Fernandez, David P. Woodruff, Taisuke Yasuda

We present tight lower bounds on the number of kernel evaluations required to approximately solve kernel ridge regression (KRR) and kernel $k$-means clustering (KKMC) on $n$ input points.

Clustering Open-Ended Question Answering +1