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About Bootstrap PDF
This document describes a method for training deep neural networks on noisy or incomplete labeled data using a bootstrapping approach. The method augments the prediction objective with a consistency term, requiring predictions to be consistent for similar inputs based on deep network features. Experiments show the approach improves robustness to label noise on MNIST, handles subjective labels better for emotion recognition, and improves detection performance on a large dataset. The consistency objective allows the model to disagree with noisy labels and relabel data during training.
Detailed Information
| Author: | ['Chaitanya K Kumar'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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