98 citations · 394 across the 24 of their papers we have counts for
26 papers
HappyMap: A Generalized Multi-calibration Method
Zhun Deng, Cynthia Dwork, Linjun Zhang
Multi-calibration is a powerful and evolving concept originating in the field of algorithmic fairness. For a predictor that estimates the outcome given covariates , and…
From Pseudorandomness to Multi-Group Fairness and Back
Cynthia Dwork, Daniel Lee, Huijia Lin +1
We identify and explore connections between the recent literature on multi-group fairness for prediction algorithms and the pseudorandomness notions of leakage-resilience and graph…
Confidence-Ranked Reconstruction of Census Microdata from Published Statistics
Travis Dick, Cynthia Dwork, Michael Kearns +4
A reconstruction attack on a private dataset takes as input some publicly accessible information about the dataset and produces a list of candidate elements of . We introduc…
Improved Generalization Guarantees in Restricted Data Models
Elbert Du, Cynthia Dwork
Differential privacy is known to protect against threats to validity incurred due to adaptive, or exploratory, data analysis -- even when the analyst adversarially searches for a s…
Scaffolding Sets
Maya Burhanpurkar, Zhun Deng, Cynthia Dwork +1
Predictors map individual instances in a population to the interval . For a collection of subsets of a population, a predictor is multi-calibrated with respect…
Outcome Indistinguishability
Cynthia Dwork, Michael P. Kim, Omer Reingold +2
Prediction algorithms assign numbers to individuals that are popularly understood as individual "probabilities" -- what is the probability of 5-year survival after cancer diagnosis…