Active learning for noisy oracle via density power divergence

DOI10.1016/j.neunet.2013.05.007zbMath1296.68146OpenAlexW2034913716WikidataQ43422796 ScholiaQ43422796MaRDI QIDQ461142

Tsuyoshi Ueno, Yasuhiro Sogawa, Yoshinobu Kawahara, Takashi Washio

Publication date: 10 October 2014

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2013.05.007

zbMATH Keywords

active learningdensity power divergencenoisy oracle

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• UCI-ml
• LIBSVM

Cites Work

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• 10.1162/153244302760185243
• Robust and efficient estimation by minimising a density power divergence
• Asymptotic Statistics
• Robust Statistics
• Soft margins for AdaBoost