A semi-supervised learning approach using pseudo labels. Implemented on Keras, evaluated on CIFAR-10.
| # True Labels | Supervised | Pseudo Labels | Pseudo Gain | # Pseudo Labels |
|---|---|---|---|---|
| 500 | 39.81% | 39.02% | -0.79% | 49500 |
| 1000 | 47.95% | 50.89% | 2.94% | 49000 |
| 5000 | 69.41% | 74.58% | 5.17% | 45000 |
| 10000 | 77.96% | 80.46% | 2.50% | 40000 |
| Pseudo Labels | ImageNet Weights | N=500 | N=1000 | N=5000 | N=10000 |
|---|---|---|---|---|---|
| No | Yes | 51.77% | 60.13% | 68.23% | 74.92% |
| No | No | 22.70% | 30.81% | 55.27% | 65.77% |
| Yes | No | 34.26% | 44.95% | 63.39% | 72.94% |
| Yes | Yes | 46.14% | 51.37% | 65.00% | 73.86% |
Dong-Hyun, Lee. Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks. 2013 http://deeplearning.net/wp-content/uploads/2013/03/pseudo_label_final.pdf
CIFAR-10を疑似ラベル（Pseudo-Label）を使った半教師あり学習で分類する https://qiita.com/koshian2/items/f4a458466b15bb91c7cb
