14 citations · 42 across the 8 of their papers we have counts for
Showing 2019Show all
2 papers · 1 filter
cs.LG2019★ 6 cited
GRASPEL: Graph Spectral Learning at Scale
Yongyu Wang, Zhiqiang Zhao, Zhuo Feng
Learning meaningful graphs from data plays important roles in many data mining and machine learning tasks, such as data representation and analysis, dimension reduction, data clust…
cs.LG2019★ 14 cited
GraphZoom: A multi-level spectral approach for accurate and scalable graph embedding
Chenhui Deng, Zhiqiang Zhao, Yongyu Wang +2
Graph embedding techniques have been increasingly deployed in a multitude of different applications that involve learning on non-Euclidean data. However, existing graph embedding m…