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Claire Lazar Reich
Claire Lazar Reich
MIT and Stanford
Verified email at stanford.edu
Title
Cited by
Cited by
Year
A possibility in algorithmic fairness: can calibration and equal error rates be reconciled?
CL Reich, S Vijaykumar
2nd Symposium on Foundations of Responsible Computing (FORC 2021), 2020
232020
Resolving the Disparate Impact of Uncertainty: Affirmative Action vs. Affirmative Information
CL Reich
arXiv preprint arXiv 2102, 2021
32021
The Disparate Impact of Uncertainty: Affirmative Action vs. Affirmative Information
CL Reich
arXiv. org Papers, 2024
12024
Classification as Direction Recovery: Improved Guarantees via Scale Invariance
S Vijaykumar, CL Reich
arXiv preprint arXiv:2205.08633, 2022
2022
Affirmative Action vs. Affirmative Information
CL Reich
arXiv preprint arXiv:2102.10019, 2021
2021
Methods to Improve Fairness and Accuracy in Machine Learning, with Applications to Financial Algorithms
C Lazar Reich
Massachusetts Institute of Technology, 2021
2021
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Articles 1–6