Linear Projection Learned from Hybrid CKA for Enhancing Distance-Based Classifiers
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-13469-3_12
Reference11 articles.
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2. Lecture Notes in Computer Science;AM Álvarez-Meza,2014
3. Brockmeier, A.J., Choi, J.S., Kriminger, E.G., Francis, J.T., Principe, J.C.: Neural decoding with kernel-based metric learning. Neural Comput. 26(6), 1080–1107 (2014). https://doi.org/10.1162/NECO_a_00591
4. Brockmeier, A.J., et al.: Information-theoretic metric learning: 2-D linear projections of neural data for visualization. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5586–5589. IEEE (2013). https://doi.org/10.1109/EMBC.2013.6610816
5. Cárdenas-Peña, D., Collazos-Huertas, D., Álvarez-Meza, A., Castellanos-Dominguez, G.: Supervised kernel approach for automated learning using general stochastic networks. Eng. Appl. Artif. Intell. 68, 10–17 (2018). https://doi.org/10.1016/j.engappai.2017.10.003
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