Generalized cross-entropy for learning from crowds based on correlated chained Gaussian processes

Generalized cross-entropy for learning from crowds based on correlated chained Gaussian processes

Machine learning applications heavily depend on labeled data provided by domain experts to train accurate models. However, the cost and time constraints associated with expert labeling often make obtaining ground truth labels impractical. Crowdsourcing offers a cost-effective alternative for collect...

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Bibliographic Details
Main Authors: J. Gil-González, G. Daza-Santacoloma, D. Cárdenas-Peña, A. Orozco-Gutiérrez, A. Álvarez-Meza
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Results in Engineering
Subjects:
Learning from crowds
Gaussian processes
Bayesian framework
Noisy labels
Non-stationary data
Generalized cross-entropy
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123024021066
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