523 citations · 1.4k across the 79 of their papers we have counts for
Showing 2014 · cs.LGShow all
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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.LG2014★ 26 cited
Similarity Learning for High-Dimensional Sparse Data
Kuan Liu, Aurélien Bellet, Fei Sha
A good measure of similarity between data points is crucial to many tasks in machine learning. Similarity and metric learning methods learn such measures automatically from data, b…
cs.LG2014★ 19 cited
Sparse Compositional Metric Learning
Yuan Shi, Aurélien Bellet, Fei Sha
We propose a new approach for metric learning by framing it as learning a sparse combination of locally discriminative metrics that are inexpensive to generate from the training da…