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- W2955284732 abstract "The present work introduces a simple scheme for classifying sequential data using blind ensembles of classifiers. Blind refers to the combiner who has no knowledge of ground-truth labels to learn the optimal classifier combination. The sequence of data along with annotator responses are modeled using a hidden Markov model (HMM). The HMM parameters are learned using a decoupling and moment-matching approach. Preliminary tests on synthetic data showcase the potential of the proposed approach." @default.
- W2955284732 created "2019-07-12" @default.
- W2955284732 creator A5005271216 @default.
- W2955284732 date "2019-06-01" @default.
- W2955284732 modified "2023-10-17" @default.
- W2955284732 title "Blind Ensemble Classification of Sequential Data" @default.
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- W2955284732 doi "https://doi.org/10.1109/dsw.2019.8755570" @default.
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