69 citations · 193 across the 7 of their papers we have counts for
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cs.LG2015★ 16 cited
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients
Bo Xie, Yingyu Liang, Le Song
Nonlinear component analysis such as kernel Principle Component Analysis (KPCA) and kernel Canonical Correlation Analysis (KCCA) are widely used in machine learning, statistics and…
cs.LG2015★ 4 cited
Communication Efficient Distributed Kernel Principal Component Analysis
Maria-Florina Balcan, Yingyu Liang, Le Song +2
Kernel Principal Component Analysis (KPCA) is a key machine learning algorithm for extracting nonlinear features from data. In the presence of a large volume of high dimensional da…