Aaron Roth

Orcid: 0000-0002-0586-0515

Affiliations:
  • University of Pennsylvania, Department of Computer and Information Science, Philadelphia, PA, USA
  • Microsoft Research New England, Cambridge, MA, USA
  • Carnegie Mellon University, Department of Computer Science, Pittsburgh, PA, USA (PhD 2010)


According to our database1, Aaron Roth authored at least 168 papers between 2008 and 2024.

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Bibliography

2024
Order of Magnitude Speedups for LLM Membership Inference.
CoRR, 2024

The Value of Ambiguous Commitments in Multi-Follower Games.
CoRR, 2024

Algorithmic Collusion Without Threats.
CoRR, 2024

Analysis of the ICML 2023 Ranking Data: Can Authors' Opinions of Their Own Papers Assist Peer Review in Machine Learning?
CoRR, 2024

Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable.
CoRR, 2024

Model Ensembling for Constrained Optimization.
CoRR, 2024

Oracle-Efficient Reinforcement Learning for Max Value Ensembles.
CoRR, 2024

Multicalibration for Confidence Scoring in LLMs.
CoRR, 2024

Repeated Contracting with Multiple Non-Myopic Agents: Policy Regret and Limited Liability.
CoRR, 2024

An Elementary Predictor Obtaining 2√T Distance to Calibration.
CoRR, 2024

Forecasting for Swap Regret for All Downstream Agents.
CoRR, 2024

Oracle Efficient Online Multicalibration and Omniprediction.
Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

Improved Differentially Private Regression via Gradient Boosting.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Membership Inference Attacks on Diffusion Models via Quantile Regression.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Multicalibration for Confidence Scoring in LLMs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Oracle Efficient Algorithms for Groupwise Regret.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Balanced Filtering via Disclosure-Controlled Proxies.
Proceedings of the 5th Symposium on Foundations of Responsible Computing, 2024

Diversified Ensembling: An Experiment in Crowdsourced Machine Learning.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023
Efficient Prior-Free Mechanisms for No-Regret Agents.
CoRR, 2023

High-Dimensional Prediction for Sequential Decision Making.
CoRR, 2023

Balanced Filtering via Non-Disclosive Proxies.
CoRR, 2023

The Scope of Multicalibration: Characterizing Multicalibration via Property Elicitation.
CoRR, 2023

Wealth Dynamics Over Generations: Analysis and Interventions.
Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

Scalable Membership Inference Attacks via Quantile Regression.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Statistical Scope of Multicalibration.
Proceedings of the International Conference on Machine Learning, 2023

Multicalibration as Boosting for Regression.
Proceedings of the International Conference on Machine Learning, 2023

Individually Fair Learning with One-Sided Feedback.
Proceedings of the International Conference on Machine Learning, 2023

Batch Multivalid Conformal Prediction.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Reconciling Individual Probability Forecasts✱.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Multicalibrated Regression for Downstream Fairness.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022
Pipeline Interventions.
Math. Oper. Res., November, 2022

Exponential Separations in Local Privacy.
ACM Trans. Algorithms, 2022

Confidence-Ranked Reconstruction of Census Microdata from Published Statistics.
CoRR, 2022

Beyond the Frontier: Fairness Without Accuracy Loss.
CoRR, 2022

Private Synthetic Data for Multitask Learning and Marginal Queries.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Practical Adversarial Multivalid Conformal Prediction.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Multivalid Learning: Means, Moments, and Prediction Intervals.
Proceedings of the 13th Innovations in Theoretical Computer Science Conference, 2022

Best vs. All: Equity and Accuracy of Standardized Test Score Reporting.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

An Algorithmic Framework for Bias Bounties.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Multiaccurate Proxies for Downstream Fairness.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Mixed Differential Privacy in Computer Vision.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Online Multiobjective Minimax Optimization and Applications.
CoRR, 2021

Rejoinder: Gaussian Differential Privacy.
CoRR, 2021

A new analysis of differential privacy's generalization guarantees (invited paper).
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Algorithms and Learning for Fair Portfolio Design.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Adaptive Machine Unlearning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentially Private Query Release Through Adaptive Projection.
Proceedings of the 38th International Conference on Machine Learning, 2021

Lexicographically Fair Learning: Algorithms and Generalization.
Proceedings of the 2nd Symposium on Foundations of Responsible Computing, 2021

An Algorithmic Framework for Fairness Elicitation.
Proceedings of the 2nd Symposium on Foundations of Responsible Computing, 2021

A User Friendly Power Tool for Deriving Online Learning Algorithms (Invited Talk).
Proceedings of the 29th Annual European Symposium on Algorithms, 2021

Moment Multicalibration for Uncertainty Estimation.
Proceedings of the Conference on Learning Theory, 2021

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning.
Proceedings of the Algorithmic Learning Theory, 2021

Minimax Group Fairness: Algorithms and Experiments.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020
Multidimensional Dynamic Pricing for Welfare Maximization.
ACM Trans. Economics and Comput., 2020

Ethical algorithm design.
SIGecom Exch., 2020

Testing differential privacy with dual interpreters.
Proc. ACM Program. Lang., 2020

Local Differential Privacy for Evolving Data.
J. Priv. Confidentiality, 2020

Convergent Algorithms for (Relaxed) Minimax Fairness.
CoRR, 2020

Guidelines for Implementing and Auditing Differentially Private Systems.
CoRR, 2020

A snapshot of the frontiers of fairness in machine learning.
Commun. ACM, 2020

Exponential Separations in Local Differential Privacy.
Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

Fair Prediction with Endogenous Behavior.
Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

Differentially Private Call Auctions and Market Impact.
Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

A New Analysis of Differential Privacy's Generalization Guarantees.
Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

Oracle Efficient Private Non-Convex Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Optimal, truthful, and private securities lending.
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Fuzzi: a three-level logic for differential privacy.
Proc. ACM Program. Lang., 2019

Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM.
J. Priv. Confidentiality, 2019

Program for TPDP 2016.
J. Priv. Confidentiality, 2019

Differentially Private Objective Perturbation: Beyond Smoothness and Convexity.
CoRR, 2019

Exponential Separations in Local Differential Privacy Through Communication Complexity.
CoRR, 2019

Eliciting and Enforcing Subjective Individual Fairness.
CoRR, 2019

Gaussian Differential Privacy.
CoRR, 2019

Average Individual Fairness: Algorithms, Generalization and Experiments.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Equal Opportunity in Online Classification with Partial Feedback.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Differentially Private Fair Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

How to Use Heuristics for Differential Privacy.
Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019

The Role of Interactivity in Local Differential Privacy.
Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019

An Empirical Study of Rich Subgroup Fairness for Machine Learning.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Downstream Effects of Affirmative Action.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Fair Algorithms for Learning in Allocation Problems.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018
Private Pareto Optimal Exchange.
ACM Trans. Economics and Comput., 2018

The Frontiers of Fairness in Machine Learning.
CoRR, 2018

Strategic Classification from Revealed Preferences.
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Learning with an Unknown Fairness Metric.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Mitigating Bias in Adaptive Data Gathering via Differential Privacy.
Proceedings of the 35th International Conference on Machine Learning, 2018

Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness.
Proceedings of the 35th International Conference on Machine Learning, 2018

Meritocratic Fairness for Infinite and Contextual Bandits.
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

2017
An Antifolk Theorem for Large Repeated Games.
ACM Trans. Economics and Comput., 2017

A framework for adaptive differential privacy.
Proc. ACM Program. Lang., 2017

A Convex Framework for Fair Regression.
CoRR, 2017

Pricing information (and its implications): technical perspective.
Commun. ACM, 2017

Guilt-free data reuse.
Commun. ACM, 2017

Fairness Incentives for Myopic Agents.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Meritocratic Fairness for Cross-Population Selection.
Proceedings of the 34th International Conference on Machine Learning, 2017

Fairness in Reinforcement Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Do prices coordinate markets?
SIGecom Exch., 2016

Private Matchings and Allocations.
SIAM J. Comput., 2016

Private algorithms for the protected in social network search.
Proc. Natl. Acad. Sci. USA, 2016

Dual Query: Practical Private Query Release for High Dimensional Data.
J. Priv. Confidentiality, 2016

Rawlsian Fairness for Machine Learning.
CoRR, 2016

Fair Learning in Markovian Environments.
CoRR, 2016

Computer-Aided Verification for Mechanism Design.
Proceedings of the Web and Internet Economics - 12th International Conference, 2016

Jointly Private Convex Programming.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

The Strange Case of Privacy in Equilibrium Models.
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

Privacy Odometers and Filters: Pay-as-you-Go Composition.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Fairness in Learning: Classic and Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Coordination Complexity: Small Information Coordinating Large Populations.
Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science, 2016

Tight Policy Regret Bounds for Improving and Decaying Bandits.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Max-Information, Differential Privacy, and Post-selection Hypothesis Testing.
Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

Adaptive Learning with Robust Generalization Guarantees.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Watch and learn: optimizing from revealed preferences feedback.
SIGecom Exch., 2015

Selling privacy at auction.
Games Econ. Behav., 2015

Auctions with online supply.
Games Econ. Behav., 2015

Privacy for the Protected (Only).
CoRR, 2015

Robust Mediators in Large Games.
CoRR, 2015

Privacy and Truthful Equilibrium Selection for Aggregative Games.
Proceedings of the Web and Internet Economics - 11th International Conference, 2015

Preserving Statistical Validity in Adaptive Data Analysis.
Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015

Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy).
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Inducing Approximately Optimal Flow Using Truthful Mediators.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Higher-Order Approximate Relational Refinement Types for Mechanism Design and Differential Privacy.
Proceedings of the 42nd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2015

Generalization in Adaptive Data Analysis and Holdout Reuse.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Accuracy for Sale: Aggregating Data with a Variance Constraint.
Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science, 2015

Online Learning and Profit Maximization from Revealed Preferences.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Differential Privacy as a Tool for Mechanism Design in Large Systems.
SIGMETRICS Perform. Evaluation Rev., 2014

The Algorithmic Foundations of Differential Privacy.
Found. Trends Theor. Comput. Sci., 2014

An Anti-Folk Theorem for Large Repeated Games with Imperfect Monitoring.
CoRR, 2014

Exploiting Metric Structure for Efficient Private Query Release.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Constrained Signaling in Auction Design.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Asymptotically truthful equilibrium selection in large congestion games.
Proceedings of the ACM Conference on Economics and Computation, 2014

Buying private data without verification.
Proceedings of the ACM Conference on Economics and Computation, 2014

Mechanism design in large games: incentives and privacy.
Proceedings of the Innovations in Theoretical Computer Science, 2014

Privately Solving Linear Programs.
Proceedings of the Automata, Languages, and Programming - 41st International Colloquium, 2014

Differential Privacy: An Economic Method for Choosing Epsilon.
Proceedings of the IEEE 27th Computer Security Foundations Symposium, 2014

2013
Privacy and mechanism design.
SIGecom Exch., 2013

Constrained signaling for welfare and revenue maximization.
SIGecom Exch., 2013

Privately Releasing Conjunctions and the Statistical Query Barrier.
SIAM J. Comput., 2013

A learning theory approach to noninteractive database privacy.
J. ACM, 2013

Bounds for the Query Complexity of Approximate Equilibria.
Electron. Colloquium Comput. Complex., 2013

Coordination When Information is Scarce: How privacy can help.
XRDS, 2013

Differential privacy for the analyst via private equilibrium computation.
Proceedings of the Symposium on Theory of Computing Conference, 2013

Beyond worst-case analysis in private singular vector computation.
Proceedings of the Symposium on Theory of Computing Conference, 2013

Fast Private Data Release Algorithms for Sparse Queries.
Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2013

Differential privacy, equilibrium, and efficient allocation of resources.
Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012
Buying private data at auction: the sensitive surveyor's problem.
SIGecom Exch., 2012

The Power of Fair Pricing Mechanisms.
Algorithmica, 2012

Efficiently Learning from Revealed Preference.
Proceedings of the Internet and Network Economics - 8th International Workshop, 2012

Take It or Leave It: Running a Survey When Privacy Comes at a Cost.
Proceedings of the Internet and Network Economics - 8th International Workshop, 2012

Iterative Constructions and Private Data Release.
Proceedings of the Theory of Cryptography - 9th Theory of Cryptography Conference, 2012

Beating randomized response on incoherent matrices.
Proceedings of the 44th Symposium on Theory of Computing Conference, 2012

Conducting truthful surveys, cheaply.
Proceedings of the 13th ACM Conference on Electronic Commerce, 2012

Distributed Private Heavy Hitters.
Proceedings of the Automata, Languages, and Programming - 39th International Colloquium, 2012

2010
Constrained Non-monotone Submodular Maximization: Offline and Secretary Algorithms.
Proceedings of the Internet and Network Economics - 6th International Workshop, 2010

Interactive privacy via the median mechanism.
Proceedings of the 42nd ACM Symposium on Theory of Computing, 2010

On the Equilibria of Alternating Move Games.
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

Differentially Private Combinatorial Optimization.
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

Differential Privacy and the Fat-Shattering Dimension of Linear Queries.
Proceedings of the Approximation, 2010

2009
The Median Mechanism: Interactive and Efficient Privacy with Multiple Queries
CoRR, 2009

Differentially Private Approximation Algorithms
CoRR, 2009

2008
The Price of Malice in Linear Congestion Games.
Proceedings of the Internet and Network Economics, 4th International Workshop, 2008

A learning theory approach to non-interactive database privacy.
Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

Regret minimization and the price of total anarchy.
Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

The Price of Stochastic Anarchy.
Proceedings of the Algorithmic Game Theory, First International Symposium, 2008


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