Unsupervised Dimensionality Reduction for Transfer Learning
Blöbaum P, Schulz A, Hammer B (2015)
In: Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Verleysen M (Ed); Louvain-la-Neuve: Ciaco: 507-512.
Konferenzbeitrag
| Veröffentlicht | Englisch
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Autor*in
Herausgeber*in
Verleysen, Michel
Einrichtung
Abstract / Bemerkung
We investigate the suitability of unsupervised dimensionality
reduction (DR) for transfer learning in the context of different representations
of the source and target domain. Essentially, unsupervised DR
establishes a link of source and target domain by representing the data in
a common latent space. We consider two settings: a linear DR of source
and target data which establishes correspondences of the data and an according
transfer, and its combination with a non-linear DR which allows to
adapt to more complex data characterised by a global non-linear structure.
Erscheinungsjahr
2015
Titel des Konferenzbandes
Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Seite(n)
507-512
Konferenz
23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015
Konferenzort
Bruges, Belgium
Konferenzdatum
2015-04-22 – 2015-04-24
ISBN
978-287587014-8
Page URI
https://pub.uni-bielefeld.de/record/2900325
Zitieren
Blöbaum P, Schulz A, Hammer B. Unsupervised Dimensionality Reduction for Transfer Learning. In: Verleysen M, ed. Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Louvain-la-Neuve: Ciaco; 2015: 507-512.
Blöbaum, P., Schulz, A., & Hammer, B. (2015). Unsupervised Dimensionality Reduction for Transfer Learning. In M. Verleysen (Ed.), Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 507-512). Louvain-la-Neuve: Ciaco.
Blöbaum, Patrick, Schulz, Alexander, and Hammer, Barbara. 2015. “Unsupervised Dimensionality Reduction for Transfer Learning”. In Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ed. Michel Verleysen, 507-512. Louvain-la-Neuve: Ciaco.
Blöbaum, P., Schulz, A., and Hammer, B. (2015). “Unsupervised Dimensionality Reduction for Transfer Learning” in Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Verleysen, M. ed. (Louvain-la-Neuve: Ciaco), 507-512.
Blöbaum, P., Schulz, A., & Hammer, B., 2015. Unsupervised Dimensionality Reduction for Transfer Learning. In M. Verleysen, ed. Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Louvain-la-Neuve: Ciaco, pp. 507-512.
P. Blöbaum, A. Schulz, and B. Hammer, “Unsupervised Dimensionality Reduction for Transfer Learning”, Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, M. Verleysen, ed., Louvain-la-Neuve: Ciaco, 2015, pp.507-512.
Blöbaum, P., Schulz, A., Hammer, B.: Unsupervised Dimensionality Reduction for Transfer Learning. In: Verleysen, M. (ed.) Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. p. 507-512. Ciaco, Louvain-la-Neuve (2015).
Blöbaum, Patrick, Schulz, Alexander, and Hammer, Barbara. “Unsupervised Dimensionality Reduction for Transfer Learning”. Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Ed. Michel Verleysen. Louvain-la-Neuve: Ciaco, 2015. 507-512.
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