Fast, Memory-Efficient Spectral Clustering with Cosine Similarity
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49018-7_50
Reference20 articles.
1. Cai, D., Chen, X.: Large scale spectral clustering via landmark-based sparse representation. IEEE Trans. Cybern. 45(8), 1669–1680 (2015)
2. Chen, G.: Scalable spectral clustering with cosine similarity. In: Proceedings of the 24th International Conference on Pattern Recognition (ICPR), Beijing, China (2018)
3. Chen, G.: A general framework for scalable spectral clustering based on document models. Pattern Recogn. Lett. 125, 488–493 (2019)
4. Chen, G., Lerman, G.: Foundations of a multi-way spectral clustering framework for hybrid linear modeling. Found. Comput. Math. (2009). https://doi.org/10.1007/s10208-009-9043-7
5. Choromanska, A., Jebara, T., Kim, H., Mohan, M., Monteleoni, C.: Fast spectral clustering via the Nyström method. In: Jain, S., Munos, R., Stephan, F., Zeugmann, T. (eds.) Algorithmic Learning Theory, pp. 367–381. Springer, Berlin, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40935-6_26
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