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Communication Dans Un Congrès Année : 2020

Optimal Laplacian Regularization for Sparse Spectral Community Detection

Résumé

Regularization of the classical Laplacian matrices was empirically shown to improve spectral clustering in sparse networks. It was observed that small regularizations are preferable, but this point was left as a heuristic argument. In this paper we formally determine a proper regularization which is intimately related to alternative state-of-the-art spectral techniques for sparse graphs.
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Dates et versions

hal-02956603 , version 1 (03-10-2020)

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Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay. Optimal Laplacian Regularization for Sparse Spectral Community Detection. ICASSP 2020 - IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, May 2020, Barcelone (virtual), Spain. ⟨10.1109/ICASSP40776.2020.9053543⟩. ⟨hal-02956603⟩
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