Official Codebase for A Tale Of Two Long Tails

If you use this software, please consider citing:

  title={A Tale Of Two Long Tails},
  author={D'souza, Daniel and Nussbaum, Zach and Agarwal, Chirag and Hooker, Sara},
  journal={arXiv preprint arXiv:2107.13098},
  year={2021}}

🚨 tldr: Examples of Atypical and Noisy Error. The former is reducible with the introduction of information and the other is not! 🚨

This repository is built using PyTorch:fire:. You can install the necessary libraries by pip install -r requirements.txt

1. Download CIFAR-10/CIFAR-100 LongTail Datasets
2. Unzip above files in folder "datasets" in main directory

The scripts to train CIFAR-10/CIFAR-100 models on all datasets is train_c10.py/train_c100.py.

Training

1. Set Variable MSP_AUG_PCT to a value between (0,1). This controls how much of the dataset to augment based on the MSP.Default is 0.2 ( Targeted Augment Variant )

2. Set Variable TRAIN_DATASET to either 'cifar10'(Original), 'N20_A20_T60'(C-Score), 'N20_A20_TX2'(Frequency)

3. Run python train_c10.py to train CIFAR-10 models

The above steps can be repeated for CIFAR-100 by using train_c100.py

CIFAR-10

CIFAR-100

Visualization Code will be added shortly.

Note that the code in this repository is licensed under MIT License. Please carefully check them before use.

If you have questions/suggestions, please feel free to email or create github issues.