A Recursive Ensemble Learning Approach With Noisy Labels or Unlabeled Data

A Recursive Ensemble Learning Approach With Noisy Labels or Unlabeled Data

For many tasks, the successful application of deep learning relies on having large amounts of training data, labeled to a high standard. But much of the data in real-world applications suffer from label noise. Data annotation is much more expensive and resource-consuming than data collection, somewh...

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Bibliographic Details
Main Authors: Yuchen Wang, Yang Yang, Yun-Xia Liu, Anil Anthony Bharath
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Noisy labels
pruning strategy
semi-supervised learning
ensemble learning
deep learning
neural networks
Online Access:https://ieeexplore.ieee.org/document/8664574/

Internet

https://ieeexplore.ieee.org/document/8664574/

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