1. Bai, L., Liang, J. Y., & Guo, Y. (2018). An ensemble clusterer of multiple fuzzy $$k$$-means clusterings to recognize arbitrarily shaped clusters. IEEE Transactions on Fuzzy Systems, 26(6), 3524–3533.
2. Basu, S., Banerjee, A. & Mooney, R. J. (2002). Semi-supervised clustering by seeding. In: Proceedings of the 19th International Conference on Machine Learning (pp. 27–34). Sydney, Australia.
3. Belkin, M., & Niyogi, P. (2008). Towards a theoretical foundation for laplacian-based manifold methods. Journal of Computer and System Sciences, 74(8), 1289–1308.
4. Belkin, M., Niyogi, P., & Sindhwani, V. (2006). Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research, 7, 2399–2434.
5. Berthelot, D., Carlini, N., Goodfellow, I. J., Papernot, N., Oliver, A., & Raffel, C. (2019). Mixmatch: a holistic approach to semi-supervised learning. In: B. C. Vancouver (Ed.), Advances in neural information processing systems 32. Annual conference on neural information processing systems (pp. 5050–5060). Canada.