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Marika Kaden

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Michael Biehl

> Home > Persons > Marika Kaden

Publications

2022
[c45]
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  dblp key:
  - conf/ida/VillmannSRSBK22
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  - https://dblp.org/rec/conf/ida/VillmannSRSBK22
Thomas Villmann, Daniel Staps, Jensun Ravichandran, Sascha Saralajew, Michael Biehl, Marika Kaden:
A Learning Vector Quantization Architecture for Transfer Learning Based Classification in Case of Multiple Sources by Means of Null-Space Evaluation. IDA 2022: 354-364
2020
[j11]
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  - journals/nca/StraatKGVLSBM20
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  - https://dblp.org/rec/journals/nca/StraatKGVLSBM20
Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert:
Learning vector quantization and relevances in complex coefficient space. Neural Comput. Appl. 32(24): 18085-18099 (2020)
2018
[j9]
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  - journals/cstat/VillmannKHB18
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  - https://dblp.org/rec/journals/cstat/VillmannKHB18
Thomas Villmann, Marika Kaden, Wieland Hermann, Michael Biehl:
Learning vector quantization classifiers for ROC-optimization. Comput. Stat. 33(3): 1173-1194 (2018)
2017
[c32]
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  - conf/wsom/StraatKGVLSBM17
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Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert:
Prototypes and matrix relevance learning in complex fourier space. WSOM 2017: 139-144
2016
[c27]
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  - conf/wsom/GayKBLV16
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  - https://dblp.org/rec/conf/wsom/GayKBLV16
Matthias Gay, Marika Kaden, Michael Biehl, Alexander Lampe, Thomas Villmann:
Complex Variants of GLVQ Based on Wirtinger's Calculus. WSOM 2016: 293-303
2015
[c25]
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  - conf/caip/VillmannKNB15
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Thomas Villmann, Marika Kaden, David Nebel, Michael Biehl:
Learning Vector Quantization with Adaptive Cost-Based Outlier-Rejection. CAIP (2) 2015: 772-782
2012
[j1]
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  - journals/ijon/KastnerHBV12
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Marika Kästner, Barbara Hammer, Michael Biehl, Thomas Villmann:
Functional relevance learning in generalized learning vector quantization. Neurocomputing 90: 85-95 (2012)
[c8]
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  - conf/icmla/KastnerNRBV12
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Marika Kästner, David Nebel, Martin Riedel, Michael Biehl, Thomas Villmann:
Differentiable Kernels in Generalized Matrix Learning Vector Quantization. ICMLA (1) 2012: 132-137
[c6]
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  - conf/wsom/BiehlKLV12
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Michael Biehl, Marika Kästner, Mandy Lange, Thomas Villmann:
Non-Euclidean Principal Component Analysis and Oja's Learning Rule - Theoretical Aspects. WSOM 2012: 23-33
2011
[c3]
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  - electronic edition @ esann.org (open access)
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  - conf/esann/KastnerHBV11
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Marika Kästner, Barbara Hammer, Michael Biehl, Thomas Villmann:
Generalized functional relevance learning vector quantization. ESANN 2011

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