3 citations · 8 across the 9 of their papers we have counts for
9 papers
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…
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…
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…
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…
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…
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.…
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…
Understanding Dynamics of Nonlinear Representation Learning and Its Application
Kenji Kawaguchi, Linjun Zhang, Zhun Deng
Representations of the world environment play a crucial role in artificial intelligence. It is often inefficient to conduct reasoning and inference directly in the space of raw sen…
Interpreting Robust Optimization via Adversarial Influence Functions
Zhun Deng, Cynthia Dwork, Jialiang Wang +1
Robust optimization has been widely used in nowadays data science, especially in adversarial training. However, little research has been done to quantify how robust optimization ch…