42 citations · 88 across the 6 of their papers we have counts for
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cs.LG2014★ 40 cited
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets
Zhiyun Lu, Avner May, Kuan Liu +8
The computational complexity of kernel methods has often been a major barrier for applying them to large-scale learning problems. We argue that this barrier can be effectively over…
cs.DC2014★ 6 cited
A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning
Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani +2
Learning sparse combinations is a frequent theme in machine learning. In this paper, we study its associated optimization problem in the distributed setting where the elements to b…