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09/12/2023
Gait Design of a Novel Arboreal Concertina Locomotion for Snake-like Robots
In this paper, we propose a novel strategy for a snake robot to move str...
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07/18/2023
Oracle Efficient Online Multicalibration and Omniprediction
A recent line of work has shown a surprising connection between multical...
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07/07/2023
Scalable Membership Inference Attacks via Quantile Regression
Membership inference attacks are designed to determine, using black box ...
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06/26/2023
Balanced Filtering via Non-Disclosive Proxies
We study the problem of non-disclosively collecting a sample of data tha...
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03/06/2023
Improved Differentially Private Regression via Gradient Boosting
We revisit the problem of differentially private squared error linear re...
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02/16/2023
The Scope of Multicalibration: Characterizing Multicalibration via Property Elicitation
We make a connection between multicalibration and property elicitation a...
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01/31/2023
Multicalibration as Boosting for Regression
We study the connection between multicalibration and boosting for square...
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11/06/2022
Confidence-Ranked Reconstruction of Census Microdata from Published Statistics
A reconstruction attack on a private dataset D takes as input some publi...
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09/30/2022
Batch Multivalid Conformal Prediction
We develop fast distribution-free conformal prediction algorithms for ob...
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09/15/2022
Private Synthetic Data for Multitask Learning and Marginal Queries
We provide a differentially private algorithm for producing synthetic da...
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09/15/2022
Wealth Dynamics Over Generations: Analysis and Interventions
We present a stylized model with feedback loops for the evolution of a p...
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09/15/2022
Multicalibrated Regression for Downstream Fairness
We show how to take a regression function f̂ that is appropriately “mult...
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09/04/2022
Reconciling Individual Probability Forecasts
Individual probabilities refer to the probabilities of outcomes that are...
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06/09/2022
Individually Fair Learning with One-Sided Feedback
We consider an online learning problem with one-sided feedback, in which...
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06/02/2022
Practical Adversarial Multivalid Conformal Prediction
We give a simple, generic conformal prediction method for sequential pre...
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03/22/2022
Mixed Differential Privacy in Computer Vision
We introduce AdaMix, an adaptive differentially private algorithm for tr...
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01/25/2022
Beyond the Frontier: Fairness Without Accuracy Loss
Notions of fair machine learning that seek to control various kinds of e...
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08/09/2021
Online Multiobjective Minimax Optimization and Applications
We introduce a simple but general online learning framework, in which at...
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07/09/2021
Multiaccurate Proxies for Downstream Fairness
We study the problem of training a model that must obey demographic fair...
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06/08/2021
Adaptive Machine Unlearning
Data deletion algorithms aim to remove the influence of deleted data poi...
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04/05/2021
Rejoinder: Gaussian Differential Privacy
In this rejoinder, we aim to address two broad issues that cover most co...
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03/11/2021
Differentially Private Query Release Through Adaptive Projection
We propose, implement, and evaluate a new algorithm for releasing answer...
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02/16/2021
Lexicographically Fair Learning: Algorithms and Generalization
We extend the notion of minimax fairness in supervised learning problems...
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02/15/2021
Best vs. All: Equity and Accuracy of Standardized Test Score Reporting
We study a game theoretic model of standardized testing for college admi...
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01/05/2021
Online Multivalid Learning: Means, Moments, and Prediction Intervals
We present a general, efficient technique for providing contextual predi...
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11/05/2020
Convergent Algorithms for (Relaxed) Minimax Fairness
We consider a recently introduced framework in which fairness is measure...
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10/08/2020
Testing Differential Privacy with Dual Interpreters
Applying differential privacy at scale requires convenient ways to check...
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08/18/2020
Moment Multicalibration for Uncertainty Estimation
We show how to achieve the notion of "multicalibration" from Hébert-John...
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07/06/2020
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
We study the data deletion problem for convex models. By leveraging tech...
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06/12/2020
Algorithms and Learning for Fair Portfolio Design
We consider a variation on the classical finance problem of optimal port...
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02/18/2020
Fair Prediction with Endogenous Behavior
There is increasing regulatory interest in whether machine learning algo...
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02/16/2020
Pipeline Interventions
We introduce the pipeline intervention problem, defined by a layered dir...
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02/13/2020
Differentially Private Call Auctions and Market Impact
We propose and analyze differentially private (DP) mechanisms for call a...
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02/10/2020
Guidelines for Implementing and Auditing Differentially Private Systems
Differential privacy is an information theoretic constraint on algorithm...
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12/12/2019
Optimal, Truthful, and Private Securities Lending
We consider a fundamental dynamic allocation problem motivated by the pr...
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09/09/2019
A New Analysis of Differential Privacy's Generalization Guarantees
We give a new proof of the "transfer theorem" underlying adaptive data a...
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09/03/2019
Differentially Private Objective Perturbation: Beyond Smoothness and Convexity
One of the most effective algorithms for differentially private learning...
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07/01/2019
Exponential Separations in Local Differential Privacy Through Communication Complexity
We prove a general connection between the communication complexity of tw...
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06/21/2019
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis
We design a general framework for answering adaptive statistical queries...
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05/29/2019
Fuzzi: A Three-Level Logic for Differential Privacy
Curators of sensitive datasets sometimes need to know whether queries ag...
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05/25/2019
Eliciting and Enforcing Subjective Individual Fairness
We revisit the notion of individual fairness first proposed by Dwork et ...
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05/25/2019
Average Individual Fairness: Algorithms, Generalization and Experiments
We propose a new family of fairness definitions for classification probl...
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05/07/2019
Gaussian Differential Privacy
Differential privacy has seen remarkable success as a rigorous and pract...
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04/07/2019
The Role of Interactivity in Local Differential Privacy
We study the power of interactivity in local differential privacy. First...
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02/06/2019
Equal Opportunity in Online Classification with Partial Feedback
We study an online classification problem with partial feedback in which...
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12/06/2018
Differentially Private Fair Learning
We design two learning algorithms that simultaneously promise differenti...
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11/19/2018
How to Use Heuristics for Differential Privacy
We develop theory for using heuristics to solve computationally hard pro...
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10/20/2018
The Frontiers of Fairness in Machine Learning
The last few years have seen an explosion of academic and popular intere...
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08/30/2018
Fair Algorithms for Learning in Allocation Problems
Settings such as lending and policing can be modeled by a centralized ag...
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08/27/2018
