Sample Complexity of Uniform Convergence for Multicalibration

Test bias: Prediction of grades of negro and white students in integrated colleges

Cleary, T. A. (1968) · 1968

Earlier work this paper cites.

Characterizations of learnability for classes of {0, …, n}-valued functions

Ben-David, S., Cesa-Bianchi, N., Haussler, D., & Long, P. M. (1995) · 1995

Earlier work this paper cites.

Asymptotic calibration

Foster, D. P., & Vohra, R. V. (1998) · 1998

Earlier work this paper cites.

From external to internal regret

Blum, A., & Mansour, Y. (2007) · 2007

Earlier work this paper cites.

Multiclass learnability and the erm principle

Daniely, A., Sabato, S., Ben-David, S., & Shalev-Shwartz, S. (2011) · 2011

Earlier work this paper cites.

Fairness through awareness

Dwork, C., Hardt, M., Pitassi, T., Reingold, O., & Zemel, R. (2012) · 2012

Earlier work this paper cites.

Understanding Machine Learning: From Theory to Algorithms

Shalev-Shwartz, S., & Ben-David, S. (2014) · 2014

Earlier work this paper cites.

Fair prediction with disparate impact: A study of bias in recidivism prediction instruments

Chouldechova, A. (2017) · 2017

Earlier work this paper cites.

Algorithmic decision making and the cost of fairness

Corbett-Davies, S., Pierson, E., Feller, A., Goel, S., & Huq, A. (2017) · 2017

Earlier work this paper cites.

Inherent Trade-Offs in the Fair Determination of Risk Scores

Kleinberg, J., Mullainathan, S., & Raghavan, M. (2017) · 2017

Cited alongside, same era.

Calibrated fairness in bandits

Liu, Y., Radanovic, G., Dimitrakakis, C., Mandal, D., & Parkes, D. C. (2017) · 2017

Cited alongside, same era.

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Pleiss, G., Raghavan, M., Wu, F., Kleinberg, J., & Weinberger, K. Q. (2017) · 2017

Cited alongside, same era.

Learning non-discriminatory predictors

Woodworth, B., Gunasekar, S., Ohannessian, M. I., & Srebro, N. (2017) · 2017

Cited alongside, same era.

Smooth calibration, leaky forecasts, finite recall, and nash dynamics

Foster, D. P., & Hart, S. (2018) · 2018

Cited alongside, same era.

Online learning with an unknown fairness metric

Gillen, S., Jung, C., Kearns, M., & Roth, A. (2018) · 2018

Cited alongside, same era.

Delayed impact of fair machine learning

Liu, L. T., Dean, S., Rolf, E., Simchowitz, M., & Hardt, M. (2018) · 2018

Later among the works it cites.

Probably approximately metric-fair learning

Yona, G., & Rothblum, G. N. (2018) · 2018

Later among the works it cites.

Envy-free classification

Balcan, M.-F. F., Dick, T., Noothigattu, R., & Procaccia, A. D. (2019) · 2019

Later among the works it cites.

Fairness and Machine Learning

Barocas, S., Hardt, M., & Narayanan, A. (2019) · 2019

Later among the works it cites.

Multiaccuracy: Black-box post-processing for fairness in classification

Kim, M. P., Ghorbani, A., & Zou, J. (2019) · 2019

Later among the works it cites.

The implicit fairness criterion of unconstrained learning

Liu, L. T., Simchowitz, M., & Hardt, M. (2019) · 2019

Later among the works it cites.