Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings

Neural Information Processing Systems 

We prove that our model can exactly represent any graph with low arboric-ity, a property that many real-world networks satisfy; our proof also applies to related models but has much greater scope than the closest prior bound, which is based on low max degree .

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