7 citations · 27 across the 8 of their papers we have counts for
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cs.LG2019★ 1 cited
Asymmetric Random Projections
Nick Ryder, Zohar Karnin, Edo Liberty
Random projections (RP) are a popular tool for reducing dimensionality while preserving local geometry. In many applications the data set to be projected is given to us in advance,…
cs.LG2019★ 7 cited
Discrepancy, Coresets, and Sketches in Machine Learning
Zohar Karnin, Edo Liberty
This paper defines the notion of class discrepancy for families of functions. It shows that low discrepancy classes admit small offline and streaming coresets. We provide general t…
cs.LG2018
ProxQuant: Quantized Neural Networks via Proximal Operators
Yu Bai, Yu-Xiang Wang, Edo Liberty
To make deep neural networks feasible in resource-constrained environments (such as mobile devices), it is beneficial to quantize models by using low-precision weights. One common…