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A Survey on Visualizations for Musical Data

Autor: Richard Khulusi, C. Meinecke, Josef Focht, Christina Gillmann, Stefan Jänicke, Jakob Kusnick

Publikováno v: Khulusi, R, Kusnick, J, Meinecke, C, Gillmann, C, Focht, J & Jänicke, S 2020, ' A Survey on Visualizations for Musical Data ', Computer Graphics Forum, vol. 39, no. 6, pp. 82-110 . https://doi.org/10.1111/cgf.13905

Digital methods are increasingly applied to store, structure and analyse vast amounts of musical data. In this context, visualization plays a crucial role, as it assists musicologists and non-expert users in data analysis and in gaining new knowledge

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b50fc4ba388f09f026b2313b5c002a7
https://doi.org/10.1111/cgf.13905

A mathematical model for the two-learners problem

Autor: Klaus-Robert Müller, Martijn Schreuder, Paul von Bünau, Carmen Vidaurre, Frank C. Meinecke, Jan Saputra Müller

Publikováno v: Journal of neural engineering. 14(3)

Objective. We present the first generic theoretical formulation of the co-adaptive learning problem and give a simple example of two interacting linear learning systems, a human and a machine. Approach. After the description of the training protocol

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::827e3238fa577ac70561976be355e870
https://pubmed.ncbi.nlm.nih.gov/28224972

Binary classification with pFDR-pFNR losses

Autor: Thorsten Dickhaus, Benjamin Blankertz, Frank C. Meinecke

Publikováno v: Biometrical Journal. 55:463-477

Connecting multiple testing with binary classification, we derive a false discovery rate-based classification approach for two-class mixture models, where the available data (represented as feature vectors) for each individual comparison take values

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e1770c7c515ff91b3452bf5ad840f0d0
https://doi.org/10.1002/bimj.201200054

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