Aaron Roth

Aaron Roth

University of Pennsylvania

H-index: 56

North America-United States

About Aaron Roth

Aaron Roth, With an exceptional h-index of 56 and a recent h-index of 50 (since 2020), a distinguished researcher at University of Pennsylvania, specializes in the field of Differential Privacy, Algorithmic Fairness, Algorithmic Game Theory, Learning Theory, Uncertainty Quantification.

His recent articles reflect a diverse array of research interests and contributions to the field:

Multicalibration for Confidence Scoring in LLMs

Scalable membership inference attacks via quantile regression

Oracle efficient online multicalibration and omniprediction

Repeated Contracting with Multiple Non-Myopic Agents: Policy Regret and Limited Liability

An Elementary Predictor Obtaining Distance to Calibration

Diversified Ensembling: An Experiment in Crowdsourced Machine Learning

Forecasting for Swap Regret for All Downstream Agents

Wealth dynamics over generations: Analysis and interventions

Aaron Roth Information

University

Position

Professor of Computer Science

Citations(all)

20981

Citations(since 2020)

16202

Cited By

10466

hIndex(all)

56

hIndex(since 2020)

50

i10Index(all)

110

i10Index(since 2020)

99

Email

University Profile Page

University of Pennsylvania

Google Scholar

View Google Scholar Profile

Aaron Roth Skills & Research Interests

Differential Privacy

Algorithmic Fairness

Algorithmic Game Theory

Learning Theory

Uncertainty Quantification

Top articles of Aaron Roth

Title

Journal

Author(s)

Publication Date

Multicalibration for Confidence Scoring in LLMs

arXiv preprint arXiv:2404.04689

Gianluca Detommaso

Martin Bertran

Riccardo Fogliato

Aaron Roth

2024/4/6

Scalable membership inference attacks via quantile regression

Advances in Neural Information Processing Systems

Martin Bertran

Shuai Tang

Aaron Roth

Michael Kearns

Jamie H Morgenstern

...

2024/2/13

Oracle efficient online multicalibration and omniprediction

Sumegha Garg

Christopher Jung

Omer Reingold

Aaron Roth

2024

Repeated Contracting with Multiple Non-Myopic Agents: Policy Regret and Limited Liability

arXiv preprint arXiv:2402.17108

Natalie Collina

Varun Gupta

Aaron Roth

2024/2/27

An Elementary Predictor Obtaining Distance to Calibration

arXiv preprint arXiv:2402.11410

Eshwar Ram Arunachaleswaran

Natalie Collina

Aaron Roth

Mirah Shi

2024/2/18

Diversified Ensembling: An Experiment in Crowdsourced Machine Learning

arXiv preprint arXiv:2402.10795

Ira Globus-Harris

Declan Harrison

Michael Kearns

Pietro Perona

Aaron Roth

2024/2/16

Forecasting for Swap Regret for All Downstream Agents

arXiv preprint arXiv:2402.08753

Aaron Roth

Mirah Shi

2024/2/13

Wealth dynamics over generations: Analysis and interventions

Krishna Acharya

Eshwar Ram Arunachaleswaran

Sampath Kannan

Aaron Roth

Juba Ziani

2023/2/8

Balanced Filtering via Non-Disclosive Proxies

arXiv preprint arXiv:2306.15083

Siqi Deng

Emily Diana

Michael Kearns

Aaron Roth

2023/6/26

High-dimensional prediction for sequential decision making

arXiv preprint arXiv:2310.17651

Georgy Noarov

Ramya Ramalingam

Aaron Roth

Stephan Xie

2023/10/26

Multicalibration as boosting for regression

arXiv preprint arXiv:2301.13767

Ira Globus-Harris

Declan Harrison

Michael Kearns

Aaron Roth

Jessica Sorrell

2023/1/31

Reconciling Individual Probability Forecasts✱

Aaron Roth

Alexander Tolbert

Scott Weinstein

2023/6/12

Oracle Efficient Algorithms for Groupwise Regret

arXiv preprint arXiv:2310.04652

Krishna Acharya

Eshwar Ram Arunachaleswaran

Sampath Kannan

Aaron Roth

Juba Ziani

2023/10/7

Reply to Sanchéz et al.: Multiplicity does not protect privacy

Proceedings of the National Academy of Sciences

Travis Dick

Cynthia Dwork

Michael Kearns

Terrance Liu

Aaron Roth

...

2023/5/2

Multicalibrated regression for downstream fairness

Ira Globus-Harris

Varun Gupta

Christopher Jung

Michael Kearns

Jamie Morgenstern

...

2023/8/8

Generating relaxed synthetic data using adaptive projection

2023/12/12

Improved differentially private regression via gradient boosting

arXiv preprint arXiv:2303.03451

Shuai Tang

Sergul Aydore

Michael Kearns

Saeyoung Rho

Aaron Roth

...

2023/3/6

The statistical scope of multicalibration

Georgy Noarov

Aaron Roth

2023/6/15

Membership Inference Attacks on Diffusion Models via Quantile Regression

arXiv preprint arXiv:2312.05140

Shuai Tang

Zhiwei Steven Wu

Sergul Aydore

Michael Kearns

Aaron Roth

2023/12/8

Confidence-ranked reconstruction of census microdata from published statistics

Proceedings of the National Academy of Sciences

Travis Dick

Cynthia Dwork

Michael Kearns

Terrance Liu

Aaron Roth

...

2023/2/21

See List of Professors in Aaron Roth University(University of Pennsylvania)

Co-Authors

H-index: 81
Michael Kearns

Michael Kearns

University of Pennsylvania

H-index: 53
Omer Reingold

Omer Reingold

Stanford University

H-index: 50
Moritz Hardt

Moritz Hardt

University of California, Berkeley

H-index: 43
Zhiwei Steven Wu

Zhiwei Steven Wu

Carnegie Mellon University

H-index: 39
Jonathan Ullman

Jonathan Ullman

Northeastern University

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