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3 Publikationen

2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933893
Feature Relevance Bounds for Ordinal Regression
Pfannschmidt, Lukas, Feature Relevance Bounds for Ordinal Regression. Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019) (). Louvain-la-Neuve, 2019
PUB | Download (ext.) | arXiv
 
2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904469
Non-Negative Kernel Sparse Coding for the Analysis of Motion Data
Hosseini, Babak, Non-Negative Kernel Sparse Coding for the Analysis of Motion Data. Artificial Neural Networks and Machine Learning – ICANN 2016 9887 (). Cham, 2016
PUB | PDF | DOI | Download (ext.) | arXiv
 
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2678214
Learning interpretable kernelized prototype-based models
Hofmann, Daniela, Learning interpretable kernelized prototype-based models. Neurocomputing 141 (). , 2014
PUB | DOI | Download (ext.) | WoS
 

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