• Corpus ID: 219558774

Node Embeddings and Exact Low-Rank Representations of Complex Networks

@article{Chanpuriya2020NodeEA,
  title={Node Embeddings and Exact Low-Rank Representations of Complex Networks},
  author={Sudhanshu Chanpuriya and Cameron Musco and Konstantinos Sotiropoulos and Charalampos E. Tsourakakis},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.05592}
}
Low-dimensional embeddings, from classical spectral embeddings to modern neural-net-inspired methods, are a cornerstone in the modeling and analysis of complex networks. Recent work by Seshadhri et al. (PNAS 2020) suggests that such embeddings cannot capture local structure arising in complex networks. In particular, they show that any network generated from a natural low-dimensional model cannot be both sparse and have high triangle density (high clustering coefficient), two hallmark… 
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