Improving Active Learning by Avoiding Ambiguous Samples
Limberg C, Wersing H, Ritter H (2018)
In: Artificial Neural Networks and Machine Learning – ICANN 2018. Kůrková V, Manolopoulos Y, Hammer B, Iliadis L, Maglogiannis I (Eds); Lecture Notes in Computer Science, 11139. Cham: Springer: 518-527.
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| Veröffentlicht | Englisch
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Autor*in
Herausgeber*in
Kůrková, Věra;
Manolopoulos, Yannis;
Hammer, Barbara;
Iliadis, Lazaros;
Maglogiannis, Ilias
Einrichtung
Erscheinungsjahr
2018
Buchtitel
Artificial Neural Networks and Machine Learning – ICANN 2018
Serientitel
Lecture Notes in Computer Science
Band
11139
Seite(n)
518-527
ISBN
978-3-030-01417-9
eISBN
978-3-030-01418-6
Page URI
https://pub.uni-bielefeld.de/record/2939050
Zitieren
Limberg C, Wersing H, Ritter H. Improving Active Learning by Avoiding Ambiguous Samples. In: Kůrková V, Manolopoulos Y, Hammer B, Iliadis L, Maglogiannis I, eds. Artificial Neural Networks and Machine Learning – ICANN 2018. Lecture Notes in Computer Science. Vol 11139. Cham: Springer; 2018: 518-527.
Limberg, C., Wersing, H., & Ritter, H. (2018). Improving Active Learning by Avoiding Ambiguous Samples. In V. Kůrková, Y. Manolopoulos, B. Hammer, L. Iliadis, & I. Maglogiannis (Eds.), Lecture Notes in Computer Science: Vol. 11139. Artificial Neural Networks and Machine Learning – ICANN 2018 (pp. 518-527). Cham: Springer. doi:10.1007/978-3-030-01418-6_51
Limberg, Christian, Wersing, Heiko, and Ritter, Helge. 2018. “Improving Active Learning by Avoiding Ambiguous Samples”. In Artificial Neural Networks and Machine Learning – ICANN 2018, ed. Věra Kůrková, Yannis Manolopoulos, Barbara Hammer, Lazaros Iliadis, and Ilias Maglogiannis, 11139:518-527. Lecture Notes in Computer Science. Cham: Springer.
Limberg, C., Wersing, H., and Ritter, H. (2018). “Improving Active Learning by Avoiding Ambiguous Samples” in Artificial Neural Networks and Machine Learning – ICANN 2018, Kůrková, V., Manolopoulos, Y., Hammer, B., Iliadis, L., and Maglogiannis, I. eds. Lecture Notes in Computer Science, vol. 11139, (Cham: Springer), 518-527.
Limberg, C., Wersing, H., & Ritter, H., 2018. Improving Active Learning by Avoiding Ambiguous Samples. In V. Kůrková, et al., eds. Artificial Neural Networks and Machine Learning – ICANN 2018. Lecture Notes in Computer Science. no.11139 Cham: Springer, pp. 518-527.
C. Limberg, H. Wersing, and H. Ritter, “Improving Active Learning by Avoiding Ambiguous Samples”, Artificial Neural Networks and Machine Learning – ICANN 2018, V. Kůrková, et al., eds., Lecture Notes in Computer Science, vol. 11139, Cham: Springer, 2018, pp.518-527.
Limberg, C., Wersing, H., Ritter, H.: Improving Active Learning by Avoiding Ambiguous Samples. In: Kůrková, V., Manolopoulos, Y., Hammer, B., Iliadis, L., and Maglogiannis, I. (eds.) Artificial Neural Networks and Machine Learning – ICANN 2018. Lecture Notes in Computer Science. 11139, p. 518-527. Springer, Cham (2018).
Limberg, Christian, Wersing, Heiko, and Ritter, Helge. “Improving Active Learning by Avoiding Ambiguous Samples”. Artificial Neural Networks and Machine Learning – ICANN 2018. Ed. Věra Kůrková, Yannis Manolopoulos, Barbara Hammer, Lazaros Iliadis, and Ilias Maglogiannis. Cham: Springer, 2018.Vol. 11139. Lecture Notes in Computer Science. 518-527.
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