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07/14/2023
On the Sublinear Regret of GP-UCB
In the kernelized bandit problem, a learner aims to sequentially compute...
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07/09/2023
Private Data Stream Analysis for Universal Symmetric Norm Estimation
We study how to release summary statistics on a data stream subject to t...
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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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07/05/2023
Meta-Learning Adversarial Bandit Algorithms
We study online meta-learning with bandit feedback, with the goal of imp...
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07/03/2023
Adaptive Principal Component Regression with Applications to Panel Data
Principal component regression (PCR) is a popular technique for fixed-de...
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06/24/2023
Adaptive Privacy Composition for Accuracy-first Mechanisms
In many practical applications of differential privacy, practitioners se...
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06/09/2023
Strategic Apple Tasting
Algorithmic decision-making in high-stakes domains often involves assign...
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06/05/2023
Generating Private Synthetic Data with Genetic Algorithms
We study the problem of efficiently generating differentially private sy...
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03/26/2023
Inverse Reinforcement Learning without Reinforcement Learning
Inverse Reinforcement Learning (IRL) is a powerful set of techniques for...
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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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03/02/2023
Choosing Public Datasets for Private Machine Learning via Gradient Subspace Distance
Differentially private stochastic gradient descent privatizes model trai...
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02/22/2023
Counterfactual Prediction Under Outcome Measurement Error
Across domains such as medicine, employment, and criminal justice, predi...
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02/16/2023
Federated Learning as a Network Effects Game
Federated Learning (FL) aims to foster collaboration among a population ...
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02/13/2023
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making
A growing literature on human-AI decision-making investigates strategies...
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11/25/2022
Strategyproof Decision-Making in Panel Data Settings and Beyond
We propose a framework for decision-making in the presence of strategic ...
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11/08/2022
Reinforcement Learning with Stepwise Fairness Constraints
AI methods are used in societally important settings, ranging from credi...
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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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09/28/2022
Meta-Learning in Games
In the literature on game-theoretic equilibrium finding, focus has mainl...
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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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08/19/2022
Game-Theoretic Algorithms for Conditional Moment Matching
A variety of problems in econometrics and machine learning, including in...
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08/03/2022
Sequence Model Imitation Learning with Unobserved Contexts
We consider imitation learning problems where the expert has access to a...
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06/16/2022
On Privacy and Personalization in Cross-Silo Federated Learning
While the application of differential privacy (DP) has been well-studied...
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06/15/2022
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints
There is a disconnect between how researchers and practitioners handle p...
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06/13/2022
Private Synthetic Data with Hierarchical Structure
We study the problem of differentially private synthetic data generation...
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06/01/2022
Incentivizing Combinatorial Bandit Exploration
Consider a bandit algorithm that recommends actions to self-interested u...
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05/30/2022
Minimax Optimal Online Imitation Learning via Replay Estimation
Online imitation learning is the problem of how best to mimic expert dem...
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05/27/2022
Meta-Learning Adversarial Bandits
We study online learning with bandit feedback across multiple tasks, wit...
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05/18/2022
Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
Child welfare agencies across the United States are turning to data-driv...
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05/13/2022
Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits
Recent years have seen the development of many open-source ML fairness t...
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04/29/2022
Extended Analysis of "How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions"
This is an extended analysis of our paper "How Child Welfare Workers Red...
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04/05/2022
Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support
AI-based decision support tools (ADS) are increasingly used to augment h...
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03/18/2022
Provably Fair Federated Learning via Bounded Group Loss
In federated learning, fair prediction across various protected groups (...
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03/10/2022
Fully Adaptive Composition in Differential Privacy
Composition is a key feature of differential privacy. Well-known advance...
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02/17/2022
Locally private nonparametric confidence intervals and sequences
This work derives methods for performing nonparametric, nonasymptotic st...
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02/10/2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization
Large-scale machine learning systems often involve data distributed acro...
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02/02/2022
Causal Imitation Learning under Temporally Correlated Noise
We develop algorithms for imitation learning from policy data that was c...
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02/02/2022
Improved Regret for Differentially Private Exploration in Linear MDP
We study privacy-preserving exploration in sequential decision-making fo...
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01/28/2022
Constrained Variational Policy Optimization for Safe Reinforcement Learning
Safe reinforcement learning (RL) aims to learn policies that satisfy cer...
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12/12/2021
Bayesian Persuasion for Algorithmic Recourse
When subjected to automated decision-making, decision subjects may strat...
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10/05/2021
A Critique of Strictly Batch Imitation Learning
Recent work by Jarrett et al. attempts to frame the problem of offline i...
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08/30/2021
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Many problems in machine learning rely on multi-task learning (MTL), in ...
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07/21/2021
Incentivizing Compliance with Algorithmic Instruments
Randomized experiments can be susceptible to selection bias due to poten...
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07/12/2021
Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses
Machine Learning algorithms often prompt individuals to strategically mo...
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06/25/2021
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
Providing privacy protection has been one of the primary motivations of ...
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06/14/2021
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
We study private synthetic data generation for query release, where the ...
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06/07/2021
Stateful Strategic Regression
Automated decision-making tools increasingly assess individuals to deter...
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03/04/2021
Of Moments and Matching: Trade-offs and Treatments in Imitation Learning
We provide a unifying view of a large family of previous imitation learn...
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03/01/2021
Information Discrepancy in Strategic Learning
We study the effects of information discrepancy across sub-populations o...
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02/21/2021
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
As machine learning black boxes are increasingly being deployed in criti...
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02/17/2021
