Distance learning in discriminative vector quantization

Schneider, P.; Biehl, M.; Hammer, Barbara

Distance learning in discriminative vector quantization

Schneider P, Biehl M, Hammer B (2009)
Neural Computation 21(10): 2942-2969.

Zeitschriftenaufsatz | Veröffentlicht | Englisch

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DOI

https://doi.org/10.1162/neco.2009.10-08-892

Autor*in

Schneider, P.; Biehl, M.; Hammer, Barbara^UniBi

Einrichtung

Technische Fakultät > AG Machine Learning

Erscheinungsjahr

2009

Zeitschriftentitel

Neural Computation

Band

21

Ausgabe

10

Seite(n)

2942-2969

ISSN

0899-7667

eISSN

1530-888X

Page URI

https://pub.uni-bielefeld.de/record/1994008

Zitieren

Schneider P, Biehl M, Hammer B. Distance learning in discriminative vector quantization. Neural Computation. 2009;21(10):2942-2969.

Schneider, P., Biehl, M., & Hammer, B. (2009). Distance learning in discriminative vector quantization. Neural Computation, 21(10), 2942-2969. https://doi.org/10.1162/neco.2009.10-08-892

Schneider, P., Biehl, M., and Hammer, Barbara. 2009. “Distance learning in discriminative vector quantization”. Neural Computation 21 (10): 2942-2969.

Schneider, P., Biehl, M., and Hammer, B. (2009). Distance learning in discriminative vector quantization. Neural Computation 21, 2942-2969.

Schneider, P., Biehl, M., & Hammer, B., 2009. Distance learning in discriminative vector quantization. Neural Computation, 21(10), p 2942-2969.

P. Schneider, M. Biehl, and B. Hammer, “Distance learning in discriminative vector quantization”, Neural Computation, vol. 21, 2009, pp. 2942-2969.

Schneider, P., Biehl, M., Hammer, B.: Distance learning in discriminative vector quantization. Neural Computation. 21, 2942-2969 (2009).

Schneider, P., Biehl, M., and Hammer, Barbara. “Distance learning in discriminative vector quantization”. Neural Computation 21.10 (2009): 2942-2969.

5 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Application of an interpretable classification model on Early Folding Residues during protein folding.
Bittrich S, Kaden M, Leberecht C, Kaiser F, Villmann T, Labudde D., BioData Min 12(), 2019
PMID: 30627219

Maintaining Security and Privacy in Health Care System Using Learning Based Deep-Q-Networks.
Mohamed Shakeel P, Baskar S, Sarma Dhulipala VR, Mishra S, Jaber MM., J Med Syst 42(10), 2018
PMID: 30171378

Prototype-based models in machine learning.
Biehl M, Hammer B, Villmann T., Wiley Interdiscip Rev Cogn Sci 7(2), 2016
PMID: 26800334

Dimensionality-Dependent Generalization Bounds for k-Dimensional Coding Schemes.
Liu T, Tao D, Xu D., Neural Comput 28(10), 2016
PMID: 27391679

Regularization in matrix relevance learning.
Schneider P, Bunte K, Stiekema H, Hammer B, Villmann T, Biehl M., IEEE Trans Neural Netw 21(5), 2010
PMID: 20236882