Bootstrapping loss function implementation

based on "Training Deep Neural Networks on Noisy Labels with Bootstrapping" https://arxiv.org/abs/1412.6596

Experiments on MNIST

Experiments on MNIST:

cd examples/mnist && python main.py run --mode hard_bootstrap --noise_fraction=0.45
cd examples/mnist && python main.py run --mode soft_bootstrap --noise_fraction=0.45
cd examples/mnist && python main.py run --mode xentropy --noise_fraction=0.45

cd examples/mnist && sh run_experiments.sh >> out 2> log

• Experiments on TRAINS
• WITH_TRAINS=True sh run_experiments.sh >> out 2> log

Requirements:

• pytorch>=1.3
• torchvision>=0.4.1
• pytorch-ignite>=0.4.2
• google fire>=0.3.1

pip install -r requirements.txt