Adapting Loss Functions to Learning Progress Improves Accuracy of Classification in Neural Networks

Andreas Knoblauch. Adapting Loss Functions to Learning Progress Improves Accuracy of Classification in Neural Networks. In Michelangelo Ceci, Sergio Flesca, Elio Masciari, Giuseppe Manco 0001, Zbigniew W. Ras, editors, Foundations of Intelligent Systems - 26th International Symposium, ISMIS 2022, Cosenza, Italy, October 3-5, 2022, Proceedings. Volume 13515 of Lecture Notes in Computer Science, pages 272-282, Springer, 2022. [doi]

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