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Efficient Interactive Multiclass Learning from Binary Feedb..:
Ngo, Hung
;
Luciw, Matthew
;
Nagi, Jawas
...
ACM Transactions on Interactive Intelligent Systems (TiiS). 4 (2014) 3 - p. 1-25 , 2014
Link:
https://dl.acm.org/doi/10.1145/2629631
RT Journal T1 <Title>Efficient Interactive Multiclass Learning from Binary Feedback</Title> UL https://suche.suub.uni-bremen.de/peid=acm-2629631&Exemplar=1&LAN=DE A1 Ngo, Hung A1 Luciw, Matthew A1 Nagi, Jawas A1 Forster, Alexander A1 Schmidhuber, Jürgen A1 Vien, Ngo Anh PB ACM YR 2014 SN 2160-6455 SN 2160-6463 K1 Human-robot interaction K1 active learning K1 contextual multiarmed bandit K1 convolutional neural networks K1 deep neural networks K1 exploration-exploitation K1 gesture recognition K1 online learning K1 partial feedback K1 upper confidence bound K1 Human-centered computing K1 Human computer interaction (HCI) K1 Interactive systems and tools K1 Computing methodologies K1 Artificial intelligence K1 Computer vision K1 Computer vision tasks JF ACM Transactions on Interactive Intelligent Systems (TiiS) VO 4 IS 3 SP 1 OP 25 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/2629631 DO https://dl.acm.org/doi/10.1145/2629631 SF ELIB - SuUB Bremen
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