Possibilistic Classification Learning Based on Contrastive Loss in Learning Vector Quantizer Networks

Author:

Musavishavazi Seyedfakhredin,Kaden Marika,Villmann Thomas

Publisher

Springer International Publishing

Reference25 articles.

1. Biehl, M., Hammer, B., Villmann, T.: Prototype-based models in machine learning. Wiley Interdiscip. Rev. Cogn. Sci. 2, 92–111 (2016)

2. Chen, C., Li, O., Tao, D., Barnett, A., Rudin, C., Su, J.: This looks like that: deep learning for interpretable image recognition. In: Wallach, H., Larochelle, H., Beygelzimer, A., d’Alché-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 32, pp. 8930–8941. Curran Associates, Inc. (2019). https://proceedings.neurips.cc/paper/2019/file/adf7ee2dcf142b0e11888e72b43fcb75-Paper.pdf

3. Cichocki, A., Zdunek, R., Phan, A., Amari, S.I.: Nonnegative Matrix and Tensor Factorizations. Wiley, Chichester (2009)

4. Devarakota, P., Mirbach, B., Ottersten, B.: Confidence estimation in classification decision: a method for detecting unseen patterns. In: International Conference on Advances Pattern Recognition (ICaPR), pp. 136–140 (2007)

5. Frénay, B., Verleysen, M.: Classification in the presence of label noise: a survey. IEEE Trans. Neural Netw. Learn. Syst. 25(5), 845–869 (2014)

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