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cs.LG2023
Faster Recalibration of an Online Predictor via Approachability
Princewill Okoroafor, Robert Kleinberg, Wen Sun
Predictive models in ML need to be trustworthy and reliable, which often at the very least means outputting calibrated probabilities. This can be particularly difficult to guarante…
cs.LG2023
On the Vulnerability of Fairness Constrained Learning to Malicious Noise
Avrim Blum, Princewill Okoroafor, Aadirupa Saha +1
We consider the vulnerability of fairness-constrained learning to small amounts of malicious noise in the training data. Konstantinov and Lampert (2021) initiated the study of this…
cs.LG2023
Non-Stochastic CDF Estimation Using Threshold Queries
Princewill Okoroafor, Vaishnavi Gupta, Robert Kleinberg +1
Estimating the empirical distribution of a scalar-valued data set is a basic and fundamental task. In this paper, we tackle the problem of estimating an empirical distribution in a…