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- W4286229968 abstract "The objective functions used in spectral clustering are usually composed of two terms: i) a term that minimizes the local quadratic variation of the cluster assignments on the graph and; ii) a term that balances the clustering partition and helps avoiding degenerate solutions. This paper shows that a graph neural network, equipped with suitable message passing layers, can generate good cluster assignments by optimizing only a balancing term. Results on attributed graph datasets show the effectiveness of the proposed approach in terms of clustering performance and computation time." @default.
- W4286229968 created "2022-07-21" @default.
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- W4286229968 date "2022-07-18" @default.
- W4286229968 modified "2023-09-28" @default.
- W4286229968 title "Simplifying Clustering with Graph Neural Networks" @default.
- W4286229968 doi "https://doi.org/10.48550/arxiv.2207.08779" @default.
- W4286229968 hasPublicationYear "2022" @default.
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