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Towards Explainable Music Emotion Recognition: The Route via Mid-level Features.

, , , and . ISMIR, page 237-243. (2019)

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On the optimization of material usage in power transformer manufacturing., , , , and . IEEE Conf. on Intelligent Systems, page 680-685. IEEE, (2016)An Evolutionary Stochastic-Local-Search Framework for One-Dimensional Cutting-Stock Problems., , and . CoRR, (2017)LEMONS: Listenable Explanations for Music recOmmeNder Systems., , , and . ECIR (2), volume 12657 of Lecture Notes in Computer Science, page 531-536. Springer, (2021)A DaQL to Monitor Data Quality in Machine Learning Applications., , , and . DEXA (1), volume 11706 of Lecture Notes in Computer Science, page 227-237. Springer, (2019)Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs., , , , and . CoRR, (2019)Two-level Explanations in Music Emotion Recognition., , and . CoRR, (2019)Receptive-Field Regularized CNNs for Music Classification and Tagging., , , , , and . CoRR, (2020)On Data Augmentation and Adversarial Risk: An Empirical Analysis., , , , , , , and . CoRR, (2020)Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs., , , , and . MediaEval, volume 2670 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)audioLIME: Listenable Explanations Using Source Separation., , and . CoRR, (2020)