Scalable Algorithms Using Sparse Storage for Parallel Spectral Clustering on GPU

Author:

He Guanlin,Vialle Stephane,Sylvestre Nicolas,Baboulin Marc

Publisher

Springer International Publishing

Reference19 articles.

1. Arthur, D., Vassilvitskii, S.: k-means++: the advantages of careful seeding. In: Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, Louisiana, USA (2007)

2. Domingos, P.: A few useful things to know about machine learning. Commun. ACM 55(10), 78–87 (2012)

3. Fender, A.: Parallel solutions for large-scale eigenvalue problems arising in graph analytics. Ph.D. thesis, Université Paris-Saclay (2017)

4. Fender, A., Emad, N., et al.: Accelerated hybrid approach for spectral problems arising in graph analytics. Procedia Comput. Sci. 80, 2338–2347 (2016)

5. He, G., Vialle, S., Baboulin, M.: Parallel and accurate k-means algorithm on CPU-GPU architectures for spectral clustering. Concurr. Comput. Pract. Exp., e6621 (2021). https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.6621

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