References
- DALL·E 2 pre-training mitigations, 2022, https://openai.com/research/dall-e-2-pre-training-mitigations.
- BERT Does Business: Implementing the BERT Model for Natural Language Processing at Wayfair, 2019, https://www.aboutwayfair.com/tech-innovation/bert-does-business-implementing-the-bert-model-for-natural-language-processing-at-wayfair.
- K. Cao, C. Wei, A. Gaidon, N. Arechiga, and T. Ma, Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss, [Online]. Available at https://proceedings.neurips.cc/paper/2019/file/621461af90cadfdaf0e8d4cc25129f91-Paper.pdf.
- T.-Y. Lin, P. Goyal, R. Girshick, K. He, and P. Dollár, Focal Loss for Dense Object Detection. arXiv, Feb. 07, 2018, http://arxiv.org/abs/1708.02002.
- Wang et al., Imbalance-XGBoost: leveraging weighted and focal losses for binary label-imbalanced classification with XGBoost, https://arxiv.org/pdf/1908.01672.pdf.
- Focal loss implementation for LightGBM, https://maxhalford.github...