222 citations · 768 across the 61 of their papers we have counts for
Showing 2018 · stat.MLShow all
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stat.ML2018★ 69 cited
Learning Role-based Graph Embeddings
Nesreen K. Ahmed, Ryan Rossi, John Boaz Lee +4
Random walks are at the heart of many existing network embedding methods. However, such algorithms have many limitations that arise from the use of random walks, e.g., the features…
stat.ML2018★ 14 cited
HONE: Higher-Order Network Embeddings
Ryan A. Rossi, Nesreen K. Ahmed, Eunyee Koh +3
This paper describes a general framework for learning Higher-Order Network Embeddings (HONE) from graph data based on network motifs. The HONE framework is highly expressive and fl…