Simplicity Bias Leads to Amplified Performance Disparities

Author:

Bell Samuel James1ORCID,Sagun Levent1ORCID

Affiliation:

1. FAIR, Meta AI, France

Publisher

ACM

Reference89 articles.

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2. What We Can't Measure, We Can't Understand

3. Eric Arazo , Diego Ortego , Paul Albert , Noel O’Connor , and Kevin Mcguinness . 2019 . Unsupervised Label Noise Modeling and Loss Correction . In Proceedings of the 36th International Conference on Machine Learning , Vol. 97 . 312–321. Eric Arazo, Diego Ortego, Paul Albert, Noel O’Connor, and Kevin Mcguinness. 2019. Unsupervised Label Noise Modeling and Loss Correction. In Proceedings of the 36th International Conference on Machine Learning, Vol. 97. 312–321.

4. Martin Arjovsky Kamalika Chaudhuri and David Lopez-Paz. 2022. Throwing Away Data Improves Worst-Class Error in Imbalanced Classification. arXiv:2205.11672. Martin Arjovsky Kamalika Chaudhuri and David Lopez-Paz. 2022. Throwing Away Data Improves Worst-Class Error in Imbalanced Classification. arXiv:2205.11672.

5. Devansh Arpit , Stanisław Jastrzębski , Nicolas Ballas , David Krueger , Emmanuel Bengio , Maxinder S. Kanwal , Tegan Maharaj , Asja Fischer , Aaron Courville , Yoshua Bengio , and Simon Lacoste-Julien . 2017 . A Closer Look at Memorization in Deep Networks . In Proceedings of the 34th International Conference on Machine Learning , Vol. 70 . 233–242. Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, and Simon Lacoste-Julien. 2017. A Closer Look at Memorization in Deep Networks. In Proceedings of the 34th International Conference on Machine Learning, Vol. 70. 233–242.

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