activity
20202026
most citedInterpreting Robust Optimization via Adversarial Influence Functions

3 citations · 8 across the 9 of their papers we have counts for

collaborators

9 papers

cs.DS2026

Differentially Private Verification of Distribution Properties

Elbert Du, Cynthia Dwork, Pranay Tankala +1

A recent line of work initiated by Chiesa and Gur and further developed by Herman and Rothblum investigates the sample and communication complexity of verifying properties of distr…

cs.LG2026

Equitable Evaluation via Elicitation

Elbert Du, Cynthia Dwork, Lunjia Hu +3

Individuals with similar qualifications and skills may vary in their demeanor, or outward manner: some tend toward self-promotion while others are modest to the point of omitting c…

cs.LG2024

Differentially Private Learning Beyond the Classical Dimensionality Regime

Cynthia Dwork, Pranay Tankala, Linjun Zhang

We initiate the study of differentially private learning in the proportional dimensionality regime, in which the number of data samples and problem dimension approach infin…

cs.CL2024

Order-Independence Without Fine Tuning

Reid McIlroy-Young, Katrina Brown, Conlan Olson +2

The development of generative language models that can create long and coherent textual outputs via autoregression has lead to a proliferation of uses and a corresponding sweep of…

cs.LG2023

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…

cs.LG2022★ 2 cited

Reinforcement Learning with Stepwise Fairness Constraints

Zhun Deng, He Sun, Zhiwei Steven Wu +2

AI methods are used in societally important settings, ranging from credit to employment to housing, and it is crucial to provide fairness in regard to algorithmic decision making.…