dblp: Aaron Roth 0001

dblp: Aaron Roth 0001
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Persons
affiliation:
University of Pennsylvania, Department of Computer and Information Science, Philadelphia, PA, USA
affiliation:
Microsoft Research New England, Cambridge, MA, USA
affiliation (PhD 2010):
Carnegie Mellon University, Department of Computer Science, Pittsburgh, PA, USA
not to be confused with:
Aaron M. Roth
Aaron Roth
0002
— US Naval Research Laboratory, Washington, D. C., USA
showing all
??
records
2026
[c136]
Natalie Collina
Ira Globus-Harris
Surbhi Goel
Varun Gupta
Aaron Roth
Mirah Shi
Collaborative Prediction: Tractable Information Aggregation via Agreement.
SODA
2026
4712-4798
[c135]
Michael Kearns
Aaron Roth
Emily Ryu
Networked Information Aggregation via Machine Learning.
SODA
2026
4799-4845
[i149]
Natalie Collina
Jiuyao Lu
Georgy Noarov
Aaron Roth
Optimal Lower Bounds for Online Multicalibration.
CoRR
abs/2601.05245
2026
[i148]
Natalie Collina
Surbhi Goel
Aaron Roth
Mirah Shi
Personalization Aids Pluralistic Alignment Under Competition.
CoRR
abs/2602.13451
2026
[i147]
Ramya Ramalingam
Osbert Bastani
Aaron Roth
Prior-Agnostic Incentive-Compatible Exploration.
CoRR
abs/2602.20465
2026
[i146]
Eric Eaton
Surbhi Goel
Marcel Hussing
Michael Kearns
Aaron Roth
Sikata Bela Sengupta
Jessica Sorrell
Model Agreement via Anchoring.
CoRR
abs/2602.23360
2026
[i145]
Sikata Bela Sengupta
Guangyi Liu
Omer Gottesman
Joseph W. Durham
Michael Kearns
Aaron Roth
Michael Caldara
Multi-Objective Reinforcement Learning for Large-Scale Tote Allocation in Human-Robot Collaborative Fulfillment Centers.
CoRR
abs/2602.24182
2026
2025
[c134]
Jiuyao Lu
Aaron Roth
Mirah Shi
Sample Efficient Omniprediction and Downstream Swap Regret for Non-Linear Losses.
COLT
2025
3829-3878
[c133]
Ira Globus-Harris
Varun Gupta
Michael Kearns
Aaron Roth
Model Ensembling for Constrained Optimization.
FORC
2025
14:1-14:17
[c132]
Tobias Leemann
Periklis Petridis
Giuseppe Vietri
Dionysis Manousakas
Aaron Roth
Sergül Aydöre
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation.
ICLR
2025
[c131]
Maxon Rubin-Toles
Maya Gambhir
Keshav Ramji
Aaron Roth
Surbhi Goel
Conformal Language Model Reasoning with Coherent Factuality.
ICLR
2025
[c130]
Eric Eaton
Marcel Hussing
Michael Kearns
Aaron Roth
Sikata Bela Sengupta
Jessica Sorrell
Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces.
ICML
2025
[c129]
Shayan Kiyani
George J. Pappas
Aaron Roth
Hamed Hassani
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents.
ICML
2025
[c128]
Georgy Noarov
Riccardo Fogliato
Martín Bertrán
Aaron Roth
Stronger Neyman Regret Guarantees for Adaptive Experimental Design.
ICML
2025
[c127]
Georgy Noarov
Ramya Ramalingam
Aaron Roth
Stephan Xie
High-Dimensional Prediction for Sequential Decision Making.
ICML
2025
[c126]
Ramya Ramalingam
Shayan Kiyani
Aaron Roth
The Relationship Between No-Regret Learning and Online Conformal Prediction.
ICML
2025
[c125]
Eshwar Ram Arunachaleswaran
Natalie Collina
Sampath Kannan
Aaron Roth
Juba Ziani
Algorithmic Collusion Without Threats.
ITCS
2025
10:1-10:21
[c124]
Eshwar Ram Arunachaleswaran
Natalie Collina
Aaron Roth
Mirah Shi
An Elementary Predictor Obtaining Distance to Calibration.
SODA
2025
1366-1370
[c123]
Natalie Collina
Surbhi Goel
Varun Gupta
Aaron Roth
Tractable Agreement Protocols.
STOC
2025
1532-1543
[e3]
Itai Ashlagi
Aaron Roth
Proceedings of the 26th ACM Conference on Economics and Computation, EC 2025, Stanford University, Stanford, CA, USA, July 7-10, 2025.
ACM
2025
, ISBN
979-8-4007-1943-1
[contents]
[i144]
Shayan Kiyani
George J. Pappas
Aaron Roth
Hamed Hassani
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents.
CoRR
abs/2502.02561
2025
[i143]
Ramya Ramalingam
Shayan Kiyani
Aaron Roth
The Relationship between No-Regret Learning and Online Conformal Prediction.
CoRR
abs/2502.10947
2025
[i142]
Eric Eaton
Marcel Hussing
Michael Kearns
Aaron Roth
Sikata Bela Sengupta
Jessica Sorrell
Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces.
CoRR
abs/2502.11828
2025
[i141]
Jiuyao Lu
Aaron Roth
Mirah Shi
Sample Efficient Omniprediction and Downstream Swap Regret for Non-Linear Losses.
CoRR
abs/2502.12564
2025
[i140]
Georgy Noarov
Riccardo Fogliato
Martín Bertrán
Aaron Roth
Stronger Neyman Regret Guarantees for Adaptive Experimental Design.
CoRR
abs/2502.17427
2025
[i139]
Natalie Collina
Ira Globus-Harris
Surbhi Goel
Varun Gupta
Aaron Roth
Mirah Shi
Collaborative Prediction: Tractable Information Aggregation via Agreement.
CoRR
abs/2504.06075
2025
[i138]
Maxon Rubin-Toles
Maya Gambhir
Keshav Ramji
Aaron Roth
Surbhi Goel
Conformal Language Model Reasoning with Coherent Factuality.
CoRR
abs/2505.17126
2025
[i137]
Michael Kearns
Aaron Roth
Emily Ryu
Networked Information Aggregation via Machine Learning.
CoRR
abs/2507.09683
2025
[i136]
Eric Eaton
Marcel Hussing
Michael Kearns
Aaron Roth
Sikata Bela Sengupta
Jessica Sorrell
Replicable Reinforcement Learning with Linear Function Approximation.
CoRR
abs/2509.08660
2025
[i135]
Yahav Bechavod
Jiuyao Lu
Aaron Roth
Online Omniprediction with Long-Term Constraints.
CoRR
abs/2509.11357
2025
[i134]
Natalie Collina
Surbhi Goel
Aaron Roth
Emily Ryu
Mirah Shi
Emergent Alignment via Competition.
CoRR
abs/2509.15090
2025
[i133]
Yahav Bechavod
Jiuyao Lu
Aaron Roth
Dynamic Regret Bounds for Online Omniprediction with Long Term Constraints.
CoRR
abs/2510.07266
2025
[i132]
Shayan Kiyani
Hamed Hassani
George J. Pappas
Aaron Roth
Robust Decision Making with Partially Calibrated Forecasts.
CoRR
abs/2510.23471
2025
[i131]
Maya Pal Gambhir
Bailey Flanigan
Aaron Roth
Near-Optimal Dropout-Robust Sortition.
CoRR
abs/2511.16897
2025
2024
[c122]
Rongting Zhang
Martín Bertrán
Aaron Roth
Order of Magnitude Speedups for LLM Membership Inference.
EMNLP
2024
4431-4443
[c121]
Ira Globus-Harris
Declan Harrison
Michael Kearns
Pietro Perona
Aaron Roth
Diversified Ensembling: An Experiment in Crowdsourced Machine Learning.
FAccT
2024
529-545
[c120]
Siqi Deng
Emily Diana
Michael Kearns
Aaron Roth
Balanced Filtering via Disclosure-Controlled Proxies.
FORC
2024
4:1-4:23
[c119]
Krishna Acharya
Eshwar Ram Arunachaleswaran
Sampath Kannan
Aaron Roth
Juba Ziani
Oracle Efficient Algorithms for Groupwise Regret.
ICLR
2024
[c118]
Gianluca Detommaso
Martin Bertran Lopez
Riccardo Fogliato
Aaron Roth
Multicalibration for Confidence Scoring in LLMs.
ICML
2024
10624-10641
[c117]
Shuai Tang
Steven Wu
Sergül Aydöre
Michael Kearns
Aaron Roth
Membership Inference Attacks on Diffusion Models via Quantile Regression.
ICML
2024
47819-47829
[c116]
Lujing Zhang
Aaron Roth
Linjun Zhang
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks.
ICML
2024
59783-59805
[c115]
Martín Bertrán
Shuai Tang
Michael Kearns
Jamie H. Morgenstern
Aaron Roth
Steven Z. Wu
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable.
NeurIPS
2024
[c114]
Marcel Hussing
Michael Kearns
Aaron Roth
Sikata Bela Sengupta
Jessica Sorrell
Oracle-Efficient Reinforcement Learning for Max Value Ensembles.
NeurIPS
2024
[c113]
Shuai Tang
Sergül Aydöre
Michael Kearns
Saeyoung Rho
Aaron Roth
Yichen Wang
Yu-Xiang Wang
Zhiwei Steven Wu
Improved Differentially Private Regression via Gradient Boosting.
SaTML
2024
33-56
[c112]
Aaron Roth
Mirah Shi
Forecasting for Swap Regret for All Downstream Agents.
EC
2024
466-488
[c111]
Natalie Collina
Aaron Roth
Han Shao
Efficient Prior-Free Mechanisms for No-Regret Agents.
EC
2024
511-541
[c110]
Natalie Collina
Varun Gupta
Aaron Roth
Repeated Contracting with Multiple Non-Myopic Agents: Policy Regret and Limited Liability.
EC
2024
640-668
[c109]
Sumegha Garg
Christopher Jung
Omer Reingold
Aaron Roth
Oracle Efficient Online Multicalibration and Omniprediction.
SODA
2024
2725-2792
[e2]
Shipra Agrawal
Aaron Roth
The Thirty Seventh Annual Conference on Learning Theory, June 30 - July 3, 2023, Edmonton, Canada.
Proceedings of Machine Learning Research
247,
PMLR
2024
[contents]
[i130]
Aaron Roth
Mirah Shi
Forecasting for Swap Regret for All Downstream Agents.
CoRR
abs/2402.08753
2024
[i129]
Ira Globus-Harris
Declan Harrison
Michael Kearns
Pietro Perona
Aaron Roth
Diversified Ensembling: An Experiment in Crowdsourced Machine Learning.
CoRR
abs/2402.10795
2024
[i128]
Eshwar Ram Arunachaleswaran
Natalie Collina
Aaron Roth
Mirah Shi
An Elementary Predictor Obtaining 2√T Distance to Calibration.
CoRR
abs/2402.11410
2024
[i127]
Natalie Collina
Varun Gupta
Aaron Roth
Repeated Contracting with Multiple Non-Myopic Agents: Policy Regret and Limited Liability.
CoRR
abs/2402.17108
2024
[i126]
Gianluca Detommaso
Martín Bertrán
Riccardo Fogliato
Aaron Roth
Multicalibration for Confidence Scoring in LLMs.
CoRR
abs/2404.04689
2024
[i125]
Lujing Zhang
Aaron Roth
Linjun Zhang
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks.
CoRR
abs/2405.02225
2024
[i124]
Marcel Hussing
Michael Kearns
Aaron Roth
Sikata Bela Sengupta
Jessica Sorrell
Oracle-Efficient Reinforcement Learning for Max Value Ensembles.
CoRR
abs/2405.16739
2024
[i123]
Ira Globus-Harris
Varun Gupta
Michael Kearns
Aaron Roth
Model Ensembling for Constrained Optimization.
CoRR
abs/2405.16752
2024
[i122]
Martín Bertrán
Shuai Tang
Michael Kearns
Jamie Morgenstern
Aaron Roth
Zhiwei Steven Wu
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable.
CoRR
abs/2405.20272
2024
[i121]
Buxin Su
Jiayao Zhang
Natalie Collina
Yuling Yan
Didong Li
Kyunghyun Cho
Jianqing Fan
Aaron Roth
Weijie J. Su
Analysis of the ICML 2023 Ranking Data: Can Authors' Opinions of Their Own Papers Assist Peer Review in Machine Learning?
CoRR
abs/2408.13430
2024
[i120]
Eshwar Ram Arunachaleswaran
Natalie Collina
Sampath Kannan
Aaron Roth
Juba Ziani
Algorithmic Collusion Without Threats.
CoRR
abs/2409.03956
2024
[i119]
Natalie Collina
Rabanus Derr
Aaron Roth
The Value of Ambiguous Commitments in Multi-Follower Games.
CoRR
abs/2409.05608
2024
[i118]
Rongting Zhang
Martín Bertrán
Aaron Roth
Order of Magnitude Speedups for LLM Membership Inference.
CoRR
abs/2409.14513
2024
[i117]
Tobias Leemann
Periklis Petridis
Giuseppe Vietri
Dionysis Manousakas
Aaron Roth
Sergül Aydöre
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation.
CoRR
abs/2410.03461
2024
[i116]
Natalie Collina
Surbhi Goel
Varun Gupta
Aaron Roth
Tractable Agreement Protocols.
CoRR
abs/2411.19791
2024
2023
[c108]
Ira Globus-Harris
Varun Gupta
Christopher Jung
Michael Kearns
Jamie Morgenstern
Aaron Roth
Multicalibrated Regression for Downstream Fairness.
AIES
2023
259-286
[c107]
Aaron Roth
Alexander Tolbert
Scott Weinstein
Reconciling Individual Probability Forecasts✱.
FAccT
2023
101-110
[c106]
Christopher Jung
Georgy Noarov
Ramya Ramalingam
Aaron Roth
Batch Multivalid Conformal Prediction.
ICLR
2023
[c105]
Yahav Bechavod
Aaron Roth
Individually Fair Learning with One-Sided Feedback.
ICML
2023
1954-1977
[c104]
Ira Globus-Harris
Declan Harrison
Michael Kearns
Aaron Roth
Jessica Sorrell
Multicalibration as Boosting for Regression.
ICML
2023
11459-11492
[c103]
Georgy Noarov
Aaron Roth
The Statistical Scope of Multicalibration.
ICML
2023
26283-26310
[c102]
Martín Bertrán
Shuai Tang
Aaron Roth
Michael Kearns
Jamie Morgenstern
Steven Wu
Scalable Membership Inference Attacks via Quantile Regression.
NeurIPS
2023
[c101]
Krishna Acharya
Eshwar Ram Arunachaleswaran
Sampath Kannan
Aaron Roth
Juba Ziani
Wealth Dynamics Over Generations: Analysis and Interventions.
SaTML
2023
42-57
[i115]
Ira Globus-Harris
Declan Harrison
Michael Kearns
Aaron Roth
Jessica Sorrell
Multicalibration as Boosting for Regression.
CoRR
abs/2301.13767
2023
[i114]
Georgy Noarov
Aaron Roth
The Scope of Multicalibration: Characterizing Multicalibration via Property Elicitation.
CoRR
abs/2302.08507
2023
[i113]
Shuai Tang
Sergül Aydöre
Michael Kearns
Saeyoung Rho
Aaron Roth
Yichen Wang
Yu-Xiang Wang
Zhiwei Steven Wu
Improved Differentially Private Regression via Gradient Boosting.
CoRR
abs/2303.03451
2023
[i112]
Siqi Deng
Emily Diana
Michael Kearns
Aaron Roth
Balanced Filtering via Non-Disclosive Proxies.
CoRR
abs/2306.15083
2023
[i111]
Martín Bertrán
Shuai Tang
Michael Kearns
Jamie Morgenstern
Aaron Roth
Zhiwei Steven Wu
Scalable Membership Inference Attacks via Quantile Regression.
CoRR
abs/2307.03694
2023
[i110]
Sumegha Garg
Christopher Jung
Omer Reingold
Aaron Roth
Oracle Efficient Online Multicalibration and Omniprediction.
CoRR
abs/2307.08999
2023
[i109]
Krishna Acharya
Eshwar Ram Arunachaleswaran
Sampath Kannan
Aaron Roth
Juba Ziani
Oracle Efficient Algorithms for Groupwise Regret.
CoRR
abs/2310.04652
2023
[i108]
Georgy Noarov
Ramya Ramalingam
Aaron Roth
Stephan Xie
High-Dimensional Prediction for Sequential Decision Making.
CoRR
abs/2310.17651
2023
[i107]
Natalie Collina
Aaron Roth
Han Shao
Efficient Prior-Free Mechanisms for No-Regret Agents.
CoRR
abs/2311.07754
2023
[i106]
Shuai Tang
Zhiwei Steven Wu
Sergül Aydöre
Michael Kearns
Aaron Roth
Membership Inference Attacks on Diffusion Models via Quantile Regression.
CoRR
abs/2312.05140
2023
2022
[j32]
Eshwar Ram Arunachaleswaran
Sampath Kannan
Aaron Roth
Juba Ziani
Pipeline Interventions.
Math. Oper. Res.
47
3207-3238
2022
[j31]
Matthew Joseph
Jieming Mao
Aaron Roth
Exponential Separations in Local Privacy.
ACM Trans. Algorithms
18
32:1-32:17
2022
[c100]
Aditya Golatkar
Alessandro Achille
Yu-Xiang Wang
Aaron Roth
Michael Kearns
Stefano Soatto
Mixed Differential Privacy in Computer Vision.
CVPR
2022
8366-8376
[c99]
Mingzi Niu
Sampath Kannan
Aaron Roth
Rakesh Vohra
Best vs. All: Equity and Accuracy of Standardized Test Score Reporting.
FAccT
2022
574-586
[c98]
Ira Globus-Harris
Michael Kearns
Aaron Roth
An Algorithmic Framework for Bias Bounties.
FAccT
2022
1106-1124
[c97]
Emily Diana
Wesley Gill
Michael Kearns
Krishnaram Kenthapadi
Aaron Roth
Saeed Sharifi-Malvajerdi
Multiaccurate Proxies for Downstream Fairness.
FAccT
2022
1207-1239
[c96]
Varun Gupta
Christopher Jung
Georgy Noarov
Mallesh M. Pai
Aaron Roth
Online Multivalid Learning: Means, Moments, and Prediction Intervals.
ITCS
2022
82:1-82:24
[c95]
Osbert Bastani
Varun Gupta
Christopher Jung
Georgy Noarov
Ramya Ramalingam
Aaron Roth
Practical Adversarial Multivalid Conformal Prediction.
NeurIPS
2022
[c94]
Daniel Lee
Georgy Noarov
Mallesh M. Pai
Aaron Roth
Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications.
NeurIPS
2022
[c93]
Giuseppe Vietri
Cédric Archambeau
Sergül Aydöre
William Brown
Michael Kearns
Aaron Roth
Amaresh Ankit Siva
Shuai Tang
Zhiwei Steven Wu
Private Synthetic Data for Multitask Learning and Marginal Queries.
NeurIPS
2022
[i105]
Ira Globus-Harris
Michael Kearns
Aaron Roth
Beyond the Frontier: Fairness Without Accuracy Loss.
CoRR
abs/2201.10408
2022
[i104]
Aditya Golatkar
Alessandro Achille
Yu-Xiang Wang
Aaron Roth
Michael Kearns
Stefano Soatto
Mixed Differential Privacy in Computer Vision.
CoRR
abs/2203.11481
2022
[i103]
Osbert Bastani
Varun Gupta
Christopher Jung
Georgy Noarov
Ramya Ramalingam
Aaron Roth
Practical Adversarial Multivalid Conformal Prediction.
CoRR
abs/2206.01067
2022
[i102]
Yahav Bechavod
Aaron Roth
Individually Fair Learning with One-Sided Feedback.
CoRR
abs/2206.04475
2022
[i101]
Aaron Roth
Alexander Tolbert
Scott Weinstein
Reconciling Individual Probability Forecasts.
CoRR
abs/2209.01687
2022
[i100]
Ira Globus-Harris
Varun Gupta
Christopher Jung
Michael Kearns
Jamie Morgenstern
Aaron Roth
Multicalibrated Regression for Downstream Fairness.
CoRR
abs/2209.07312
2022
[i99]
Krishna Acharya
Eshwar Ram Arunachaleswaran
Sampath Kannan
Aaron Roth
Juba Ziani
Wealth Dynamics Over Generations: Analysis and Interventions.
CoRR
abs/2209.07375
2022
[i98]
Giuseppe Vietri
Cédric Archambeau
Sergül Aydöre
William Brown
Michael Kearns
Aaron Roth
Amaresh Ankit Siva
Shuai Tang
Zhiwei Steven Wu
Private Synthetic Data for Multitask Learning and Marginal Queries.
CoRR
abs/2209.07400
2022
[i97]
Christopher Jung
Georgy Noarov
Ramya Ramalingam
Aaron Roth
Batch Multivalid Conformal Prediction.
CoRR
abs/2209.15145
2022
[i96]
Travis Dick
Cynthia Dwork
Michael Kearns
Terrance Liu
Aaron Roth
Giuseppe Vietri
Zhiwei Steven Wu
Confidence-Ranked Reconstruction of Census Microdata from Published Statistics.
CoRR
abs/2211.03128
2022
2021
[c92]
Emily Diana
Wesley Gill
Michael Kearns
Krishnaram Kenthapadi
Aaron Roth
Minimax Group Fairness: Algorithms and Experiments.
AIES
2021
66-76
[c91]
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning.
ALT
2021
931-962
[c90]
Christopher Jung
Changhwa Lee
Mallesh M. Pai
Aaron Roth
Rakesh Vohra
Moment Multicalibration for Uncertainty Estimation.
COLT
2021
2634-2678
[c89]
Aaron Roth
A User Friendly Power Tool for Deriving Online Learning Algorithms (Invited Talk).
ESA
2021
2:1-2:1
[c88]
Christopher Jung
Michael Kearns
Seth Neel
Aaron Roth
Logan Stapleton
Zhiwei Steven Wu
An Algorithmic Framework for Fairness Elicitation.
FORC
2021
2:1-2:19
[c87]
Emily Diana
Wesley Gill
Ira Globus-Harris
Michael Kearns
Aaron Roth
Saeed Sharifi-Malvajerdi
Lexicographically Fair Learning: Algorithms and Generalization.
FORC
2021
6:1-6:23
[c86]
Sergül Aydöre
William Brown
Michael Kearns
Krishnaram Kenthapadi
Luca Melis
Aaron Roth
Amaresh Ankit Siva
Differentially Private Query Release Through Adaptive Projection.
ICML
2021
457-467
[c85]
Eshwar Ram Arunachaleswaran
Sampath Kannan
Aaron Roth
Juba Ziani
Pipeline Interventions.
ITCS
2021
8:1-8:20
[c84]
Varun Gupta
Christopher Jung
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Chris Waites
Adaptive Machine Unlearning.
NeurIPS
2021
16319-16330
[c83]
Emily Diana
Travis Dick
Hadi Elzayn
Michael Kearns
Aaron Roth
Zachary Schutzman
Saeed Sharifi-Malvajerdi
Juba Ziani
Algorithms and Learning for Fair Portfolio Design.
EC
2021
371-389
[c82]
Christopher Jung
Katrina Ligett
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Moshe Shenfeld
A new analysis of differential privacy's generalization guarantees (invited paper).
STOC
2021
[i95]
Varun Gupta
Christopher Jung
Georgy Noarov
Mallesh M. Pai
Aaron Roth
Online Multivalid Learning: Means, Moments, and Prediction Intervals.
CoRR
abs/2101.01739
2021
[i94]
Sampath Kannan
Mingzi Niu
Aaron Roth
Rakesh Vohra
Best vs. All: Equity and Accuracy of Standardized Test Score Reporting.
CoRR
abs/2102.07809
2021
[i93]
Emily Diana
Wesley Gill
Ira Globus-Harris
Michael Kearns
Aaron Roth
Saeed Sharifi-Malvajerdi
Lexicographically Fair Learning: Algorithms and Generalization.
CoRR
abs/2102.08454
2021
[i92]
Sergül Aydöre
William Brown
Michael Kearns
Krishnaram Kenthapadi
Luca Melis
Aaron Roth
Amaresh Ankit Siva
Differentially Private Query Release Through Adaptive Projection.
CoRR
abs/2103.06641
2021
[i91]
Jinshuo Dong
Aaron Roth
Weijie J. Su
Rejoinder: Gaussian Differential Privacy.
CoRR
abs/2104.01987
2021
[i90]
Varun Gupta
Christopher Jung
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Chris Waites
Adaptive Machine Unlearning.
CoRR
abs/2106.04378
2021
[i89]
Emily Diana
Wesley Gill
Michael Kearns
Krishnaram Kenthapadi
Aaron Roth
Saeed Sharifi-Malvajerdi
Multiaccurate Proxies for Downstream Fairness.
CoRR
abs/2107.04423
2021
[i88]
Georgy Noarov
Mallesh M. Pai
Aaron Roth
Online Multiobjective Minimax Optimization and Applications.
CoRR
abs/2108.03837
2021
2020
[j30]
Alexandra Chouldechova
Aaron Roth
A snapshot of the frontiers of fairness in machine learning.
Commun. ACM
63
82-89
2020
[j29]
Matthew Joseph
Aaron Roth
Jonathan R. Ullman
Bo Waggoner
Local Differential Privacy for Evolving Data.
J. Priv. Confidentiality
10
2020
[j28]
Hengchu Zhang
Edo Roth
Andreas Haeberlen
Benjamin C. Pierce
Aaron Roth
Testing differential privacy with dual interpreters.
Proc. ACM Program. Lang.
OOPSLA
165:1-165:26
2020
[j27]
Michael Kearns
Aaron Roth
Ethical algorithm design.
SIGecom Exch.
18
31-36
2020
[j26]
Aaron Roth
Aleksandrs Slivkins
Jonathan R. Ullman
Zhiwei Steven Wu
Multidimensional Dynamic Pricing for Welfare Maximization.
ACM Trans. Economics and Comput.
6:1-6:35
2020
[c81]
Ryan Rogers
Aaron Roth
Adam D. Smith
Nathan Srebro
Om Thakkar
Blake E. Woodworth
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis.
AISTATS
2020
2830-2840
[c80]
Emily Diana
Michael Kearns
Seth Neel
Aaron Roth
Optimal, truthful, and private securities lending.
ICAIF
2020
48:1-48:8
[c79]
Seth Neel
Aaron Roth
Giuseppe Vietri
Zhiwei Steven Wu
Oracle Efficient Private Non-Convex Optimization.
ICML
2020
7243-7252
[c78]
Christopher Jung
Katrina Ligett
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Moshe Shenfeld
A New Analysis of Differential Privacy's Generalization Guarantees.
ITCS
2020
31:1-31:17
[c77]
Emily Diana
Hadi Elzayn
Michael Kearns
Aaron Roth
Saeed Sharifi-Malvajerdi
Juba Ziani
Differentially Private Call Auctions and Market Impact.
EC
2020
541-583
[c76]
Christopher Jung
Sampath Kannan
Changhwa Lee
Mallesh M. Pai
Aaron Roth
Rakesh Vohra
Fair Prediction with Endogenous Behavior.
EC
2020
677-678
[c75]
Matthew Joseph
Jieming Mao
Aaron Roth
Exponential Separations in Local Differential Privacy.
SODA
2020
515-527
[e1]
Aaron Roth
1st Symposium on Foundations of Responsible Computing, FORC 2020, Harvard University, Cambridge, MA, USA (Virtual Conference), June 1-3, 2020.
LIPIcs
156,
Schloss Dagstuhl - Leibniz-Zentrum für Informatik
2020
, ISBN
978-3-95977-142-9
[contents]
[i87]
Daniel Kifer
Solomon Messing
Aaron Roth
Abhradeep Thakurta
Danfeng Zhang
Guidelines for Implementing and Auditing Differentially Private Systems.
CoRR
abs/2002.04049
2020
[i86]
Emily Diana
Hadi Elzayn
Michael J. Kearns
Aaron Roth
Saeed Sharifi-Malvajerdi
Juba Ziani
Differentially Private Call Auctions and Market Impact.
CoRR
abs/2002.05699
2020
[i85]
Eshwar Ram Arunachaleswaran
Sampath Kannan
Aaron Roth
Juba Ziani
Pipeline Interventions.
CoRR
abs/2002.06592
2020
[i84]
Christopher Jung
Sampath Kannan
Changhwa Lee
Mallesh M. Pai
Aaron Roth
Rakesh Vohra
Fair Prediction with Endogenous Behavior.
CoRR
abs/2002.07147
2020
[i83]
Emily Diana
Travis Dick
Hadi Elzayn
Michael J. Kearns
Aaron Roth
Zachary Schutzman
Saeed Sharifi-Malvajerdi
Juba Ziani
Algorithms and Learning for Fair Portfolio Design.
CoRR
abs/2006.07281
2020
[i82]
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning.
CoRR
abs/2007.02923
2020
[i81]
Christopher Jung
Changhwa Lee
Mallesh M. Pai
Aaron Roth
Rakesh Vohra
Moment Multicalibration for Uncertainty Estimation.
CoRR
abs/2008.08037
2020
[i80]
Hengchu Zhang
Edo Roth
Andreas Haeberlen
Benjamin C. Pierce
Aaron Roth
Testing Differential Privacy with Dual Interpreters.
CoRR
abs/2010.04126
2020
[i79]
Emily Diana
Wesley Gill
Michael Kearns
Krishnaram Kenthapadi
Aaron Roth
Convergent Algorithms for (Relaxed) Minimax Fairness.
CoRR
abs/2011.03108
2020
2019
[j25]
Gilles Barthe
Christos Dimitrakakis
Marco Gaboardi
Andreas Haeberlen
Aaron Roth
Aleksandra B. Slavkovic
Program for TPDP 2016.
J. Priv. Confidentiality
2019
[j24]
Zhiwei Steven Wu
Aaron Roth
Katrina Ligett
Bo Waggoner
Seth Neel
Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM.
J. Priv. Confidentiality
2019
[j23]
Hengchu Zhang
Edo Roth
Andreas Haeberlen
Benjamin C. Pierce
Aaron Roth
Fuzzi: a three-level logic for differential privacy.
Proc. ACM Program. Lang.
ICFP
93:1-93:28
2019
[c74]
Michael J. Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
An Empirical Study of Rich Subgroup Fairness for Machine Learning.
FAT
2019
100-109
[c73]
Hadi Elzayn
Shahin Jabbari
Christopher Jung
Michael J. Kearns
Seth Neel
Aaron Roth
Zachary Schutzman
Fair Algorithms for Learning in Allocation Problems.
FAT
2019
170-179
[c72]
Sampath Kannan
Aaron Roth
Juba Ziani
Downstream Effects of Affirmative Action.
FAT
2019
240-248
[c71]
Seth Neel
Aaron Roth
Zhiwei Steven Wu
How to Use Heuristics for Differential Privacy.
FOCS
2019
72-93
[c70]
Matthew Joseph
Jieming Mao
Seth Neel
Aaron Roth
The Role of Interactivity in Local Differential Privacy.
FOCS
2019
94-105
[c69]
Matthew Jagielski
Michael J. Kearns
Jieming Mao
Alina Oprea
Aaron Roth
Saeed Sharifi-Malvajerdi
Jonathan R. Ullman
Differentially Private Fair Learning.
ICML
2019
3000-3008
[c68]
Saeed Sharifi-Malvajerdi
Michael J. Kearns
Aaron Roth
Average Individual Fairness: Algorithms, Generalization and Experiments.
NeurIPS
2019
8240-8249
[c67]
Yahav Bechavod
Katrina Ligett
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
Equal Opportunity in Online Classification with Partial Feedback.
NeurIPS
2019
8972-8982
[i78]
Yahav Bechavod
Katrina Ligett
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
Equal Opportunity in Online Classification with Partial Feedback.
CoRR
abs/1902.02242
2019
[i77]
Matthew Joseph
Jieming Mao
Seth Neel
Aaron Roth
The Role of Interactivity in Local Differential Privacy.
CoRR
abs/1904.03564
2019
[i76]
Jinshuo Dong
Aaron Roth
Weijie J. Su
Gaussian Differential Privacy.
CoRR
abs/1905.02383
2019
[i75]
Michael J. Kearns
Aaron Roth
Saeed Sharifi-Malvajerdi
Average Individual Fairness: Algorithms, Generalization and Experiments.
CoRR
abs/1905.10607
2019
[i74]
Christopher Jung
Michael J. Kearns
Seth Neel
Aaron Roth
Logan Stapleton
Zhiwei Steven Wu
Eliciting and Enforcing Subjective Individual Fairness.
CoRR
abs/1905.10660
2019
[i73]
Hengchu Zhang
Edo Roth
Andreas Haeberlen
Benjamin C. Pierce
Aaron Roth
Fuzzi: A Three-Level Logic for Differential Privacy.
CoRR
abs/1905.12594
2019
[i72]
Ryan Rogers
Aaron Roth
Adam D. Smith
Nathan Srebro
Om Thakkar
Blake E. Woodworth
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis.
CoRR
abs/1906.09231
2019
[i71]
Matthew Joseph
Jieming Mao
Aaron Roth
Exponential Separations in Local Differential Privacy Through Communication Complexity.
CoRR
abs/1907.00813
2019
[i70]
Seth Neel
Aaron Roth
Giuseppe Vietri
Zhiwei Steven Wu
Differentially Private Objective Perturbation: Beyond Smoothness and Convexity.
CoRR
abs/1909.01783
2019
[i69]
Christopher Jung
Katrina Ligett
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Moshe Shenfeld
A New Analysis of Differential Privacy's Generalization Guarantees.
CoRR
abs/1909.03577
2019
[i68]
Emily Diana
Michael J. Kearns
Seth Neel
Aaron Roth
Optimal, Truthful, and Private Securities Lending.
CoRR
abs/1912.06202
2019
2018
[j22]
Sampath Kannan
Jamie Morgenstern
Ryan Rogers
Aaron Roth
Private Pareto Optimal Exchange.
ACM Trans. Economics and Comput.
3-4
12:1-12:25
2018
[c66]
Matthew Joseph
Michael J. Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
Meritocratic Fairness for Infinite and Contextual Bandits.
AIES
2018
158-163
[c65]
Michael J. Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness.
ICML
2018
2569-2577
[c64]
Seth Neel
Aaron Roth
Mitigating Bias in Adaptive Data Gathering via Differential Privacy.
ICML
2018
3717-3726
[c63]
Sampath Kannan
Jamie Morgenstern
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem.
NeurIPS
2018
2231-2241
[c62]
Matthew Joseph
Aaron Roth
Jonathan R. Ullman
Bo Waggoner
Local Differential Privacy for Evolving Data.
NeurIPS
2018
2381-2390
[c61]
Stephen Gillen
Christopher Jung
Michael J. Kearns
Aaron Roth
Online Learning with an Unknown Fairness Metric.
NeurIPS
2018
2605-2614
[c60]
Jinshuo Dong
Aaron Roth
Zachary Schutzman
Bo Waggoner
Zhiwei Steven Wu
Strategic Classification from Revealed Preferences.
EC
2018
55-70
[i67]
Sampath Kannan
Jamie Morgenstern
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem.
CoRR
abs/1801.03423
2018
[i66]
Stephen Gillen
Christopher Jung
Michael J. Kearns
Aaron Roth
Online Learning with an Unknown Fairness Metric.
CoRR
abs/1802.06936
2018
[i65]
Matthew Joseph
Aaron Roth
Jonathan R. Ullman
Bo Waggoner
Local Differential Privacy for Evolving Data.
CoRR
abs/1802.07128
2018
[i64]
Seth Neel
Aaron Roth
Mitigating Bias in Adaptive Data Gathering via Differential Privacy.
CoRR
abs/1806.02329
2018
[i63]
Michael J. Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
An Empirical Study of Rich Subgroup Fairness for Machine Learning.
CoRR
abs/1808.08166
2018
[i62]
Sampath Kannan
Aaron Roth
Juba Ziani
Downstream Effects of Affirmative Action.
CoRR
abs/1808.09004
2018
[i61]
Hadi Elzayn
Shahin Jabbari
Christopher Jung
Michael J. Kearns
Seth Neel
Aaron Roth
Zachary Schutzman
Fair Algorithms for Learning in Allocation Problems.
CoRR
abs/1808.10549
2018
[i60]
Alexandra Chouldechova
Aaron Roth
The Frontiers of Fairness in Machine Learning.
CoRR
abs/1810.08810
2018
[i59]
Seth Neel
Aaron Roth
Zhiwei Steven Wu
How to Use Heuristics for Differential Privacy.
CoRR
abs/1811.07765
2018
[i58]
Matthew Jagielski
Michael J. Kearns
Jieming Mao
Alina Oprea
Aaron Roth
Saeed Sharifi-Malvajerdi
Jonathan R. Ullman
Differentially Private Fair Learning.
CoRR
abs/1812.02696
2018
2017
[j21]
Cynthia Dwork
Vitaly Feldman
Moritz Hardt
Toniann Pitassi
Omer Reingold
Aaron Roth
Guilt-free data reuse.
Commun. ACM
60
86-93
2017
[j20]
Aaron Roth
Pricing information (and its implications): technical perspective.
Commun. ACM
60
12
78
2017
[j19]
Daniel Winograd-Cort
Andreas Haeberlen
Aaron Roth
Benjamin C. Pierce
A framework for adaptive differential privacy.
Proc. ACM Program. Lang.
ICFP
10:1-10:29
2017
[j18]
Mallesh M. Pai
Aaron Roth
Jonathan R. Ullman
An Antifolk Theorem for Large Repeated Games.
ACM Trans. Economics and Comput.
10:1-10:20
2017
[c59]
Shahin Jabbari
Matthew Joseph
Michael J. Kearns
Jamie Morgenstern
Aaron Roth
Fairness in Reinforcement Learning.
ICML
2017
1617-1626
[c58]
Michael J. Kearns
Aaron Roth
Zhiwei Steven Wu
Meritocratic Fairness for Cross-Population Selection.
ICML
2017
1828-1836
[c57]
Katrina Ligett
Seth Neel
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM.
NIPS
2017
2566-2576
[c56]
Sampath Kannan
Michael J. Kearns
Jamie Morgenstern
Mallesh M. Pai
Aaron Roth
Rakesh V. Vohra
Zhiwei Steven Wu
Fairness Incentives for Myopic Agents.
EC
2017
369-386
[c55]
Aaron Roth
Aleksandrs Slivkins
Jonathan R. Ullman
Zhiwei Steven Wu
Multidimensional Dynamic Pricing for Welfare Maximization.
EC
2017
519-536
[i57]
Sampath Kannan
Michael J. Kearns
Jamie Morgenstern
Mallesh M. Pai
Aaron Roth
Rakesh V. Vohra
Zhiwei Steven Wu
Fairness Incentives for Myopic Agents.
CoRR
abs/1705.02321
2017
[i56]
Katrina Ligett
Seth Neel
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM.
CoRR
abs/1705.10829
2017
[i55]
Richard Berk
Hoda Heidari
Shahin Jabbari
Matthew Joseph
Michael J. Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
A Convex Framework for Fair Regression.
CoRR
abs/1706.02409
2017
[i54]
Jinshuo Dong
Aaron Roth
Zachary Schutzman
Bo Waggoner
Zhiwei Steven Wu
Strategic Classification from Revealed Preferences.
CoRR
abs/1710.07887
2017
[i53]
Michael J. Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness.
CoRR
abs/1711.05144
2017
2016
[j17]
Marco Gaboardi
Emilio Jesús Gallego Arias
Justin Hsu
Aaron Roth
Zhiwei Steven Wu
Dual Query: Practical Private Query Release for High Dimensional Data.
J. Priv. Confidentiality
2016
[j16]
Michael J. Kearns
Aaron Roth
Zhiwei Steven Wu
Grigory Yaroslavtsev
Private algorithms for the protected in social network search.
Proc. Natl. Acad. Sci. USA
113
913-918
2016
[j15]
Justin Hsu
Zhiyi Huang
Aaron Roth
Tim Roughgarden
Zhiwei Steven Wu
Private Matchings and Allocations.
SIAM J. Comput.
45
1953-1984
2016
[j14]
Justin Hsu
Jamie Morgenstern
Ryan M. Rogers
Aaron Roth
Rakesh Vohra
Do prices coordinate markets?
SIGecom Exch.
15
84-88
2016
[j13]
Paul W. Goldberg
Aaron Roth
Bounds for the Query Complexity of Approximate Equilibria.
ACM Trans. Economics and Comput.
24:1-24:25
2016
[c54]
Rachel Cummings
Katrina Ligett
Kobbi Nissim
Aaron Roth
Zhiwei Steven Wu
Adaptive Learning with Robust Generalization Guarantees.
COLT
2016
772-814
[c53]
Ryan M. Rogers
Aaron Roth
Adam D. Smith
Om Thakkar
Max-Information, Differential Privacy, and Post-selection Hypothesis Testing.
FOCS
2016
487-494
[c52]
Hoda Heidari
Michael J. Kearns
Aaron Roth
Tight Policy Regret Bounds for Improving and Decaying Bandits.
IJCAI
2016
1562-1570
[c51]
Rachel Cummings
Katrina Ligett
Jaikumar Radhakrishnan
Aaron Roth
Zhiwei Steven Wu
Coordination Complexity: Small Information Coordinating Large Populations.
ITCS
2016
281-290
[c50]
Matthew Joseph
Michael J. Kearns
Jamie Morgenstern
Aaron Roth
Fairness in Learning: Classic and Contextual Bandits.
NIPS
2016
325-333
[c49]
Shahin Jabbari
Ryan M. Rogers
Aaron Roth
Zhiwei Steven Wu
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs.
NIPS
2016
1570-1578
[c48]
Ryan M. Rogers
Salil P. Vadhan
Aaron Roth
Jonathan R. Ullman
Privacy Odometers and Filters: Pay-as-you-Go Composition.
NIPS
2016
1921-1929
[c47]
Rachel Cummings
Katrina Ligett
Mallesh M. Pai
Aaron Roth
The Strange Case of Privacy in Equilibrium Models.
EC
2016
659
[c46]
Justin Hsu
Zhiyi Huang
Aaron Roth
Zhiwei Steven Wu
Jointly Private Convex Programming.
SODA
2016
580-599
[c45]
Justin Hsu
Jamie Morgenstern
Ryan M. Rogers
Aaron Roth
Rakesh Vohra
Do prices coordinate markets?
STOC
2016
440-453
[c44]
Aaron Roth
Jonathan R. Ullman
Zhiwei Steven Wu
Watch and learn: optimizing from revealed preferences feedback.
STOC
2016
949-962
[c43]
Gilles Barthe
Marco Gaboardi
Emilio Jesús Gallego Arias
Justin Hsu
Aaron Roth
Pierre-Yves Strub
Computer-Aided Verification for Mechanism Design.
WINE
2016
279-293
[i52]
Rachel Cummings
Katrina Ligett
Kobbi Nissim
Aaron Roth
Zhiwei Steven Wu
Adaptive Learning with Robust Generalization Guarantees.
CoRR
abs/1602.07726
2016
[i51]
Ryan M. Rogers
Aaron Roth
Adam D. Smith
Om Thakkar
Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing.
CoRR
abs/1604.03924
2016
[i50]
Matthew Joseph
Michael J. Kearns
Jamie Morgenstern
Aaron Roth
Fairness in Learning: Classic and Contextual Bandits.
CoRR
abs/1605.07139
2016
[i49]
Ryan M. Rogers
Aaron Roth
Jonathan R. Ullman
Salil P. Vadhan
Privacy Odometers and Filters: Pay-as-you-Go Composition.
CoRR
abs/1605.08294
2016
[i48]
Aaron Roth
Aleksandrs Slivkins
Jonathan R. Ullman
Zhiwei Steven Wu
Multidimensional Dynamic Pricing for Welfare Maximization.
CoRR
abs/1607.05397
2016
[i47]
Matthew Joseph
Michael J. Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
Rawlsian Fairness for Machine Learning.
CoRR
abs/1610.09559
2016
[i46]
Shahin Jabbari
Matthew Joseph
Michael J. Kearns
Jamie Morgenstern
Aaron Roth
Fair Learning in Markovian Environments.
CoRR
abs/1611.03071
2016
2015
[j12]
Moshe Babaioff
Liad Blumrosen
Aaron Roth
Auctions with online supply.
Games Econ. Behav.
90
227-246
2015
[j11]
Arpita Ghosh
Aaron Roth
Selling privacy at auction.
Games Econ. Behav.
91
334-346
2015
[j10]
Aaron Roth
Jonathan R. Ullman
Zhiwei Steven Wu
Watch and learn: optimizing from revealed preferences feedback.
SIGecom Exch.
14
101-104
2015
[c42]
Kareem Amin
Rachel Cummings
Lili Dworkin
Michael J. Kearns
Aaron Roth
Online Learning and Profit Maximization from Revealed Preferences.
AAAI
2015
770-776
[c41]
Rachel Cummings
Katrina Ligett
Aaron Roth
Zhiwei Steven Wu
Juba Ziani
Accuracy for Sale: Aggregating Data with a Variance Constraint.
ITCS
2015
317-324
[c40]
Cynthia Dwork
Vitaly Feldman
Moritz Hardt
Toniann Pitassi
Omer Reingold
Aaron Roth
Generalization in Adaptive Data Analysis and Holdout Reuse.
NIPS
2015
2350-2358
[c39]
Gilles Barthe
Marco Gaboardi
Emilio Jesús Gallego Arias
Justin Hsu
Aaron Roth
Pierre-Yves Strub
Higher-Order Approximate Relational Refinement Types for Mechanism Design and Differential Privacy.
POPL
2015
55-68
[c38]
Sampath Kannan
Jamie Morgenstern
Ryan M. Rogers
Aaron Roth
Private Pareto Optimal Exchange.
EC
2015
261-278
[c37]
Ryan M. Rogers
Aaron Roth
Jonathan R. Ullman
Zhiwei Steven Wu
Inducing Approximately Optimal Flow Using Truthful Mediators.
EC
2015
471-488
[c36]
Sampath Kannan
Jamie Morgenstern
Aaron Roth
Zhiwei Steven Wu
Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy).
SODA
2015
1890-1903
[c35]
Cynthia Dwork
Vitaly Feldman
Moritz Hardt
Toniann Pitassi
Omer Reingold
Aaron Leon Roth
Preserving Statistical Validity in Adaptive Data Analysis.
STOC
2015
117-126
[c34]
Rachel Cummings
Michael J. Kearns
Aaron Roth
Zhiwei Steven Wu
Privacy and Truthful Equilibrium Selection for Aggregative Games.
WINE
2015
286-299
[i45]
Ryan M. Rogers
Aaron Roth
Jonathan R. Ullman
Zhiwei Steven Wu
Inducing Approximately Optimal Flow Using Truthful Mediators.
CoRR
abs/1502.04019
2015
[i44]
Gilles Barthe
Marco Gaboardi
Emilio Jesús Gallego Arias
Justin Hsu
Aaron Roth
Pierre-Yves Strub
Computer-aided verification in mechanism design.
CoRR
abs/1502.04052
2015
[i43]
Aaron Roth
Jonathan R. Ullman
Zhiwei Steven Wu
Watch and Learn: Optimizing from Revealed Preferences Feedback.
CoRR
abs/1504.01033
2015
[i42]
Michael J. Kearns
Aaron Roth
Zhiwei Steven Wu
Grigory Yaroslavtsev
Privacy for the Protected (Only).
CoRR
abs/1506.00242
2015
[i41]
Shahin Jabbari
Ryan M. Rogers
Aaron Roth
Zhiwei Steven Wu
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs.
CoRR
abs/1506.02162
2015
[i40]
Cynthia Dwork
Vitaly Feldman
Moritz Hardt
Toniann Pitassi
Omer Reingold
Aaron Roth
Generalization in Adaptive Data Analysis and Holdout Reuse.
CoRR
abs/1506.02629
2015
[i39]
Rachel Cummings
Katrina Ligett
Mallesh M. Pai
Aaron Roth
The Strange Case of Privacy in Equilibrium Models.
CoRR
abs/1508.03080
2015
[i38]
Rachel Cummings
Katrina Ligett
Jaikumar Radhakrishnan
Aaron Roth
Zhiwei Steven Wu
Coordination Complexity: Small Information Coordinating Large Populations.
CoRR
abs/1508.03735
2015
[i37]
Justin Hsu
Jamie Morgenstern
Ryan M. Rogers
Aaron Roth
Rakesh Vohra
Do Prices Coordinate Markets?
CoRR
abs/1511.00925
2015
[i36]
Michael J. Kearns
Mallesh M. Pai
Ryan M. Rogers
Aaron Roth
Jonathan R. Ullman
Robust Mediators in Large Games.
CoRR
abs/1512.02698
2015
2014
[j9]
Cynthia Dwork
Aaron Roth
The Algorithmic Foundations of Differential Privacy.
Found. Trends Theor. Comput. Sci.
3-4
211-407
2014
[j8]
Aaron Roth
Differential Privacy as a Tool for Mechanism Design in Large Systems.
SIGMETRICS Perform. Evaluation Rev.
42
39
2014
[c33]
Justin Hsu
Marco Gaboardi
Andreas Haeberlen
Sanjeev Khanna
Arjun Narayan
Benjamin C. Pierce
Aaron Roth
Differential Privacy: An Economic Method for Choosing Epsilon.
CSF
2014
398-410
[c32]
Justin Hsu
Aaron Roth
Tim Roughgarden
Jonathan R. Ullman
Privately Solving Linear Programs.
ICALP (1)
2014
612-624
[c31]
Marco Gaboardi
Emilio Jesús Gallego Arias
Justin Hsu
Aaron Roth
Zhiwei Steven Wu
Dual Query: Practical Private Query Release for High Dimensional Data.
ICML
2014
1170-1178
[c30]
Michael J. Kearns
Mallesh M. Pai
Aaron Roth
Jonathan R. Ullman
Mechanism design in large games: incentives and privacy.
ITCS
2014
403-410
[c29]
Paul W. Goldberg
Aaron Roth
Bounds for the query complexity of approximate equilibria.
EC
2014
639-656
[c28]
Ryan M. Rogers
Aaron Roth
Asymptotically truthful equilibrium selection in large congestion games.
EC
2014
771-782
[c27]
Arpita Ghosh
Katrina Ligett
Aaron Roth
Grant Schoenebeck
Buying private data without verification.
EC
2014
931-948
[c26]
Zhiyi Huang
Aaron Roth
Exploiting Metric Structure for Efficient Private Query Release.
SODA
2014
523-534
[c25]
Shaddin Dughmi
Nicole Immorlica
Aaron Roth
Constrained Signaling in Auction Design.
SODA
2014
1341-1357
[c24]
Justin Hsu
Zhiyi Huang
Aaron Roth
Tim Roughgarden
Zhiwei Steven Wu
Private matchings and allocations.
STOC
2014
21-30
[i35]
Marco Gaboardi
Emilio Jesús Gallego Arias
Justin Hsu
Aaron Roth
Zhiwei Steven Wu
Dual Query: Practical Private Query Release for High Dimensional Data.
CoRR
abs/1402.1526
2014
[i34]
Mallesh M. Pai
Aaron Roth
Jonathan R. Ullman
An Anti-Folk Theorem for Large Repeated Games with Imperfect Monitoring.
CoRR
abs/1402.2801
2014
[i33]
Justin Hsu
Marco Gaboardi
Andreas Haeberlen
Sanjeev Khanna
Arjun Narayan
Benjamin C. Pierce
Aaron Roth
Differential Privacy: An Economic Method for Choosing Epsilon.
CoRR
abs/1402.3329
2014
[i32]
Justin Hsu
Aaron Roth
Tim Roughgarden
Jonathan R. Ullman
Privately Solving Linear Programs.
CoRR
abs/1402.3631
2014
[i31]
Arpita Ghosh
Katrina Ligett
Aaron Roth
Grant Schoenebeck
Buying Private Data without Verification.
CoRR
abs/1404.6003
2014
[i30]
Sampath Kannan
Jamie Morgenstern
Aaron Roth
Zhiwei Steven Wu
Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy).
CoRR
abs/1407.2640
2014
[i29]
Sampath Kannan
Jamie Morgenstern
Ryan M. Rogers
Aaron Roth
Private Pareto Optimal Exchange.
CoRR
abs/1407.2641
2014
[i28]
Gilles Barthe
Marco Gaboardi
Emilio Jesús Gallego Arias
Justin Hsu
Aaron Roth
Pierre-Yves Strub
Higher-Order Approximate Relational Refinement Types for Mechanism Design and Differential Privacy.
CoRR
abs/1407.6845
2014
[i27]
Kareem Amin
Rachel Cummings
Lili Dworkin
Michael J. Kearns
Aaron Roth
Online Learning and Profit Maximization from Revealed Preferences.
CoRR
abs/1407.7294
2014
[i26]
Rachel Cummings
Michael J. Kearns
Aaron Roth
Zhiwei Steven Wu
Privacy and Truthful Equilibrium Selection for Aggregative Games.
CoRR
abs/1407.7740
2014
[i25]
Justin Hsu
Zhiyi Huang
Aaron Roth
Zhiwei Steven Wu
Jointly Private Convex Programming.
CoRR
abs/1411.0998
2014
[i24]
Cynthia Dwork
Vitaly Feldman
Moritz Hardt
Toniann Pitassi
Omer Reingold
Aaron Roth
Preserving Statistical Validity in Adaptive Data Analysis.
CoRR
abs/1411.2664
2014
2013
[j7]
Aaron Roth
Coordination When Information is Scarce: How privacy can help.
XRDS
20
14-16
2013
[j6]
Avrim Blum
Katrina Ligett
Aaron Roth
A learning theory approach to noninteractive database privacy.
J. ACM
60
12:1-12:25
2013
[j5]
Anupam Gupta
Moritz Hardt
Aaron Roth
Jonathan R. Ullman
Privately Releasing Conjunctions and the Statistical Query Barrier.
SIAM J. Comput.
42
1494-1520
2013
[j4]
Mallesh M. Pai
Aaron Roth
Privacy and mechanism design.
SIGecom Exch.
12
8-29
2013
[j3]
Shaddin Dughmi
Nicole Immorlica
Aaron Roth
Constrained signaling for welfare and revenue maximization.
SIGecom Exch.
12
53-56
2013
[c23]
Aaron Roth
Differential privacy, equilibrium, and efficient allocation of resources.
Allerton
2013
1593-1597
[c22]
Avrim Blum
Aaron Roth
Fast Private Data Release Algorithms for Sparse Queries.
APPROX-RANDOM
2013
395-410
[c21]
Moritz Hardt
Aaron Roth
Beyond worst-case analysis in private singular vector computation.
STOC
2013
331-340
[c20]
Justin Hsu
Aaron Roth
Jonathan R. Ullman
Differential privacy for the analyst via private equilibrium computation.
STOC
2013
341-350
[i23]
Shaddin Dughmi
Nicole Immorlica
Aaron Roth
Constrained Signaling for Welfare and Revenue Maximization.
CoRR
abs/1302.4713
2013
[i22]
Mallesh M. Pai
Aaron Roth
Privacy and Mechanism Design.
CoRR
abs/1306.2083
2013
[i21]
Justin Hsu
Zhiyi Huang
Aaron Roth
Tim Roughgarden
Zhiwei Steven Wu
Private Matchings and Allocations.
CoRR
abs/1311.2828
2013
[i20]
Paul W. Goldberg
Aaron Roth
Bounds for the Query Complexity of Approximate Equilibria.
Electron. Colloquium Comput. Complex.
TR13
Article TR13-136
2013
2012
[j2]
Christine Chung
Katrina Ligett
Kirk Pruhs
Aaron Roth
The Power of Fair Pricing Mechanisms.
Algorithmica
63
634-644
2012
[j1]
Aaron Roth
Buying private data at auction: the sensitive surveyor's problem.
SIGecom Exch.
11
1-8
2012
[c19]
Justin Hsu
Sanjeev Khanna
Aaron Roth
Distributed Private Heavy Hitters.
ICALP (1)
2012
461-472
[c18]
Aaron Roth
Grant Schoenebeck
Conducting truthful surveys, cheaply.
EC
2012
826-843
[c17]
Moritz Hardt
Aaron Roth
Beating randomized response on incoherent matrices.
STOC
2012
1255-1268
[c16]
Anupam Gupta
Aaron Roth
Jonathan R. Ullman
Iterative Constructions and Private Data Release.
TCC
2012
339-356
[c15]
Morteza Zadimoghaddam
Aaron Roth
Efficiently Learning from Revealed Preference.
WINE
2012
114-127
[c14]
Katrina Ligett
Aaron Roth
Take It or Leave It: Running a Survey When Privacy Comes at a Cost.
WINE
2012
378-391
[i19]
Katrina Ligett
Aaron Roth
Take it or Leave it: Running a Survey when Privacy Comes at a Cost.
CoRR
abs/1202.4741
2012
[i18]
Justin Hsu
Sanjeev Khanna
Aaron Roth
Distributed Private Heavy Hitters.
CoRR
abs/1202.4910
2012
[i17]
Aaron Roth
Grant Schoenebeck
Conducting Truthful Surveys, Cheaply.
CoRR
abs/1203.0353
2012
[i16]
Justin Hsu
Aaron Roth
Jonathan R. Ullman
Differential Privacy for the Analyst via Private Equilibrium Computation.
CoRR
abs/1211.0877
2012
[i15]
Moritz Hardt
Aaron Roth
Beyond Worst-Case Analysis in Private Singular Vector Computation.
CoRR
abs/1211.0975
2012
[i14]
Morteza Zadimoghaddam
Aaron Roth
Efficiently Learning from Revealed Preference.
CoRR
abs/1211.4150
2012
[i13]
Zhiyi Huang
Aaron Roth
Exploiting Metric Structure for Efficient Private Query Release.
CoRR
abs/1211.7302
2012
2011
[c13]
Arpita Ghosh
Aaron Roth
Selling privacy at auction.
EC
2011
199-208
[c12]
Anupam Gupta
Moritz Hardt
Aaron Roth
Jonathan R. Ullman
Privately releasing conjunctions and the statistical query barrier.
STOC
2011
803-812
[i12]
Anupam Gupta
Aaron Roth
Jonathan R. Ullman
Iterative Constructions and Private Data Release.
CoRR
abs/1107.3731
2011
[i11]
Avrim Blum
Katrina Ligett
Aaron Roth
A Learning Theory Approach to Non-Interactive Database Privacy.
CoRR
abs/1109.2229
2011
[i10]
Moritz Hardt
Aaron Roth
Beating Randomized Response on Incoherent Matrices.
CoRR
abs/1111.0623
2011
[i9]
Avrim Blum
Aaron Roth
Fast Private Data Release Algorithms for Sparse Queries.
CoRR
abs/1111.6842
2011
2010
[c11]
Aaron Roth
Differential Privacy and the Fat-Shattering Dimension of Linear Queries.
APPROX-RANDOM
2010
683-695
[c10]
Christine Chung
Katrina Ligett
Kirk Pruhs
Aaron Roth
The Power of Fair Pricing Mechanisms.
LATIN
2010
554-564
[c9]
Moshe Babaioff
Liad Blumrosen
Aaron Roth
Auctions with online supply.
EC
2010
13-22
[c8]
Aaron Roth
Maria-Florina Balcan
Adam Kalai
Yishay Mansour
On the Equilibria of Alternating Move Games.
SODA
2010
805-816
[c7]
Anupam Gupta
Katrina Ligett
Frank McSherry
Aaron Roth
Kunal Talwar
Differentially Private Combinatorial Optimization.
SODA
2010
1106-1125
[c6]
Aaron Roth
Tim Roughgarden
Interactive privacy via the median mechanism.
STOC
2010
765-774
[c5]
Anupam Gupta
Aaron Roth
Grant Schoenebeck
Kunal Talwar
Constrained Non-monotone Submodular Maximization: Offline and Secretary Algorithms.
WINE
2010
246-257
[i8]
Anupam Gupta
Aaron Roth
Grant Schoenebeck
Kunal Talwar
Constrained Non-Monotone Submodular Maximization: Offline and Secretary Algorithms.
CoRR
abs/1003.1517
2010
[i7]
Aaron Roth
Differential Privacy and the Fat-Shattering Dimension of Linear Queries.
CoRR
abs/1004.3205
2010
[i6]
Anupam Gupta
Moritz Hardt
Aaron Roth
Jonathan R. Ullman
Privately Releasing Conjunctions and the Statistical Query Barrier.
CoRR
abs/1011.1296
2010
[i5]
Arpita Ghosh
Aaron Roth
Selling Privacy at Auction.
CoRR
abs/1011.1375
2010
2009
[i4]
Kunal Talwar
Anupam Gupta
Katrina Ligett
Frank McSherry
Aaron Roth
Differentially Private Combinatorial Optimization.
Parameterized complexity and approximation algorithms
2009
[i3]
Anupam Gupta
Katrina Ligett
Frank McSherry
Aaron Roth
Kunal Talwar
Differentially Private Approximation Algorithms.
CoRR
abs/0903.4510
2009
[i2]
Moshe Babaioff
Liad Blumrosen
Aaron Roth
Auctions with Online Supply.
CoRR
abs/0905.3429
2009
[i1]
Aaron Roth
Tim Roughgarden
The Median Mechanism: Interactive and Efficient Privacy with Multiple Queries.
CoRR
abs/0911.1813
2009
2008
[c4]
Christine Chung
Katrina Ligett
Kirk Pruhs
Aaron Roth
The Price of Stochastic Anarchy.
SAGT
2008
303-314
[c3]
Avrim Blum
MohammadTaghi Hajiaghayi
Katrina Ligett
Aaron Roth
Regret minimization and the price of total anarchy.
STOC
2008
373-382
[c2]
Avrim Blum
Katrina Ligett
Aaron Roth
A learning theory approach to non-interactive database privacy.
STOC
2008
609-618
[c1]
Aaron Roth
The Price of Malice in Linear Congestion Games.
WINE
2008
118-125
Krishna Acharya
[c119]
[c101]
[i109]
[i99]
Alessandro Achille
[c100]
[i104]
Shipra Agrawal
0001
[e2]
Kareem Amin
0002
[c42]
[i27]
Cédric Archambeau
[c93]
[i98]
Emilio Jesús Gallego Arias
[j17]
[c43]
[c39]
[i44]
[c31]
[i35]
[i28]
Eshwar Ram Arunachaleswaran
[c125]
[c124]
[c119]
[i128]
[i120]
[c101]
[i109]
[j32]
[i99]
[c85]
[i85]
Itai Ashlagi
[e3]
Sergül Aydöre
[c132]
[c117]
[c113]
[i117]
[i113]
[i106]
[c93]
[i98]
[c86]
[i92]
10
Moshe Babaioff
[j12]
[c9]
[i2]
11
Maria-Florina Balcan
[c8]
12
Gilles Barthe
[j25]
[c43]
[c39]
[i44]
[i28]
13
Osbert Bastani
[i147]
[c95]
[i103]
14
Yahav Bechavod
[i135]
[i133]
[c105]
[i102]
[c67]
[i78]
15
Richard Berk
[i55]
16
Martín Bertrán
[c128]
[i140]
[c122]
[c115]
[i126]
[i122]
[i118]
[c102]
[i111]
17
Avrim Blum
[j6]
[c22]
[i11]
[i9]
[c3]
[c2]
18
Liad Blumrosen
[j12]
[c9]
[i2]
19
William Brown
[c93]
[i98]
[c86]
[i92]
20
Michael Caldara
[i145]
21
Kyunghyun Cho
[i121]
22
Alexandra Chouldechova
[j30]
[i60]
23
Christine Chung
0001
[j2]
[c10]
[c4]
24
Natalie Collina
[c136]
[i149]
[i148]
[c125]
[c124]
[c123]
[i139]
[i134]
[c111]
[c110]
[i128]
[i127]
[i121]
[i120]
[i119]
[i116]
[i107]
25
Rachel Cummings
[c54]
[c51]
[c47]
[i52]
[c42]
[c41]
[c34]
[i39]
[i38]
[i27]
[i26]
26
Siqi Deng
[c120]
[i112]
27
Rabanus Derr
[i119]
28
Gianluca Detommaso
[c118]
[i126]
29
Emily Diana
[c120]
[i112]
[c97]
[c92]
[c87]
[c83]
[i93]
[i89]
[c80]
[c77]
[i86]
[i83]
[i79]
[i68]
30
Travis Dick
[i96]
[c83]
[i83]
31
Christos Dimitrakakis
[j25]
32
Jinshuo Dong
[i91]
[i76]
[c60]
[i54]
33
Shaddin Dughmi
[c25]
[j3]
[i23]
34
Joseph W. Durham
[i145]
35
Cynthia Dwork
[i96]
[j21]
[c40]
[c35]
[i40]
[j9]
[i24]
36
Lili Dworkin
[c42]
[i27]
37
Eric Eaton
[i146]
[c130]
[i142]
[i136]
38
Hadi Elzayn
[c83]
[c77]
[i86]
[i83]
[c73]
[i61]
39
Jianqing Fan
[i121]
40
Vitaly Feldman
[j21]
[c40]
[c35]
[i40]
[i24]
41
Bailey Flanigan
[i131]
42
Riccardo Fogliato
[c128]
[i140]
[c118]
[i126]
43
Marco Gaboardi
[j25]
[j17]
[c43]
[c39]
[i44]
[c33]
[c31]
[i35]
[i33]
[i28]
44
Maya Gambhir
[c131]
[i138]
45
Maya Pal Gambhir
[i131]
46
Sumegha Garg
[c109]
[i110]
47
Arpita Ghosh
[j11]
[c27]
[i31]
[c13]
[i5]
48
Wesley Gill
[c97]
[c92]
[c87]
[i93]
[i89]
[i79]
49
Stephen Gillen
[c61]
[i66]
50
Ira Globus-Harris
[c136]
[c133]
[i139]
[c121]
[i129]
[i123]
[c108]
[c104]
[i115]
[c98]
[i105]
[i100]
[c87]
[i93]
51
Surbhi Goel
[c136]
[i148]
[i146]
[c131]
[c123]
[i139]
[i138]
[i134]
[i116]
52
Aditya Golatkar
[c100]
[i104]
53
Paul W. Goldberg
[j13]
[c29]
[i20]
54
Omer Gottesman
[i145]
55
Anupam Gupta
0001
[j5]
[c16]
[c12]
[i12]
[c7]
[c5]
[i8]
[i6]
[i4]
[i3]
56
Varun Gupta
0006
[c136]
[c133]
[c123]
[i139]
[c110]
[i127]
[i123]
[i116]
[c108]
[c96]
[c95]
[i103]
[i100]
[c84]
[i95]
[i90]
57
Andreas Haeberlen
[j28]
[i80]
[j25]
[j23]
[i73]
[j19]
[c33]
[i33]
58
Mohammad Hajiaghayi
aka: MohammadTaghi Hajiaghayi
[c3]
59
Moritz Hardt
[j21]
[c40]
[c35]
[i40]
[i24]
[j5]
[c21]
[c17]
[i15]
[c12]
[i10]
[i6]
60
Declan Harrison
[c121]
[i129]
[c104]
[i115]
61
Seyed Hamed Hassani
aka: Hamed Hassani
[c129]
[i144]
[i132]
62
Hoda Heidari
[i55]
[c52]
63
Justin Hsu
[j17]
[j15]
[j14]
[c46]
[c45]
[c43]
[c39]
[i44]
[i37]
[c33]
[c32]
[c31]
[c24]
[i35]
[i33]
[i32]
[i28]
[i25]
[c20]
[i21]
[c19]
[i18]
[i16]
64
Zhiyi Huang
0002
[j15]
[c46]
[c26]
[c24]
[i25]
[i21]
[i13]
65
Marcel Hussing
[i146]
[c130]
[i142]
[i136]
[c114]
[i124]
66
Nicole Immorlica
[c25]
[j3]
[i23]
67
Shahin Jabbari
[c73]
[i61]
[c59]
[i55]
[c49]
[i46]
[i41]
68
Matthew Jagielski
[c69]
[i58]
69
Matthew Joseph
[j31]
[j29]
[c75]
[c70]
[i77]
[i71]
[c66]
[c62]
[i65]
[c59]
[i55]
[c50]
[i50]
[i47]
[i46]
70
Christopher Jung
0001
[c109]
[c108]
[c106]
[i110]
[c96]
[c95]
[i103]
[i100]
[i97]
[c90]
[c88]
[c84]
[c82]
[i95]
[i90]
[c78]
[c76]
[i84]
[i81]
[c73]
[i74]
[i69]
[c61]
[i66]
[i61]
71
Adam Tauman Kalai
aka: Adam Kalai
[c8]
72
Sampath Kannan
[c125]
[c119]
[i120]
[c101]
[i109]
[j32]
[c99]
[i99]
[c85]
[i94]
[c76]
[i85]
[i84]
[c72]
[j22]
[c63]
[i67]
[i62]
[c56]
[i57]
[c38]
[c36]
[i30]
[i29]
73
Michael Kearns
aka: Michael J. Kearns
[c135]
[i146]
[i145]
[c133]
[c130]
[i142]
[i137]
[i136]
[c121]
[c120]
[c117]
[c115]
[c114]
[c113]
[i129]
[i124]
[i123]
[i122]
[c108]
[c104]
[c102]
[i115]
[i113]
[i112]
[i111]
[i106]
[c100]
[c98]
[c97]
[c93]
[i105]
[i104]
[i100]
[i98]
[i96]
[c92]
[c88]
[c87]
[c86]
[c83]
[i93]
[i92]
[i89]
[j27]
[c80]
[c77]
[i86]
[i83]
[i79]
[c74]
[c73]
[c69]
[c68]
[i75]
[i74]
[i68]
[c66]
[c65]
[c61]
[i66]
[i63]
[i61]
[i58]
[c59]
[c58]
[c56]
[i57]
[i55]
[i53]
[j16]
[c52]
[c50]
[i50]
[i47]
[i46]
[c42]
[c34]
[i42]
[i36]
[c30]
[i27]
[i26]
74
Krishnaram Kenthapadi
[c97]
[c92]
[c86]
[i92]
[i89]
[i79]
75
Sanjeev Khanna
[c33]
[i33]
[c19]
[i18]
76
Daniel Kifer
[i87]
77
Shayan Kiyani
[c129]
[c126]
[i144]
[i143]
[i132]
78
Changhwa Lee
[c90]
[c76]
[i84]
[i81]
79
Daniel Lee
[c94]
80
Tobias Leemann
[c132]
[i117]
81
Didong Li
[i121]
82
Katrina Ligett
[c82]
[c78]
[j24]
[c67]
[i78]
[i69]
[c57]
[i56]
[c54]
[c51]
[c47]
[i52]
[c41]
[i39]
[i38]
[c27]
[i31]
[j6]
[j2]
[c14]
[i19]
[i11]
[c10]
[c7]
[i4]
[i3]
[c4]
[c3]
[c2]
83
Guangyi Liu
[i145]
84
Terrance Liu
[i96]
85
Martin Bertran Lopez
[c118]
86
Jiuyao Lu
[i149]
[c134]
[i141]
[i135]
[i133]
87
Dionysis Manousakas
[c132]
[i117]
88
Yishay Mansour
[c8]
89
Jieming Mao
[j31]
[c75]
[c70]
[c69]
[i77]
[i71]
[i58]
90
Frank McSherry
[c7]
[i4]
[i3]
91
Luca Melis
[c86]
[i92]
92
Solomon Messing
[i87]
93
Jamie Morgenstern
aka: Jamie H. Morgenstern
[c115]
[i122]
[c108]
[c102]
[i111]
[i100]
[j22]
[c66]
[c63]
[i67]
[c59]
[c56]
[i57]
[i55]
[j14]
[c50]
[c45]
[i50]
[i47]
[i46]
[c38]
[c36]
[i37]
[i30]
[i29]
94
Arjun Narayan
[c33]
[i33]
95
Seth Neel
[c91]
[c88]
[c84]
[c82]
[i90]
[c80]
[c79]
[c78]
[i82]
[j24]
[c74]
[c73]
[c71]
[c70]
[i77]
[i74]
[i70]
[i69]
[i68]
[c66]
[c65]
[c64]
[i64]
[i63]
[i61]
[i59]
[c57]
[i56]
[i55]
[i53]
[i47]
96
Kobbi Nissim
[c54]
[i52]
97
Mingzi Niu
[c99]
[i94]
98
Georgy Noarov
[i149]
[c128]
[c127]
[i140]
[c106]
[c103]
[i114]
[i108]
[c96]
[c95]
[c94]
[i103]
[i97]
[i95]
[i88]
99
Alina Oprea
[c69]
[i58]
100
Mallesh M. Pai
[c96]
[c94]
[c90]
[i95]
[i88]
[c76]
[i84]
[i81]
[j18]
[c56]
[i57]
[c47]
[i39]
[i36]
[c30]
[i34]
[j4]
[i22]
101
George J. Pappas
[c129]
[i144]
[i132]
102
Pietro Perona
[c121]
[i129]
103
Periklis Petridis
[c132]
[i117]
104
Benjamin C. Pierce
[j28]
[i80]
[j23]
[i73]
[j19]
[c33]
[i33]
105
Toniann Pitassi
[j21]
[c40]
[c35]
[i40]
[i24]
106
Kirk Pruhs
[j2]
[c10]
[c4]
107
Jaikumar Radhakrishnan
[c51]
[i38]
108
Ramya Ramalingam
[i147]
[c127]
[c126]
[i143]
[c106]
[i108]
[c95]
[i103]
[i97]
109
Keshav Ramji
[c131]
[i138]
110
Omer Reingold
[c109]
[i110]
[j21]
[c40]
[c35]
[i40]
[i24]
111
Saeyoung Rho
[c113]
[i113]
112
Ryan Rogers
0002
aka: Ryan M. Rogers
[c81]
[i72]
[j22]
[j14]
[c53]
[c49]
[c48]
[c45]
[i51]
[i49]
[c38]
[c37]
[i45]
[i41]
[i37]
[i36]
[c28]
[i29]
113
Edo Roth
[j28]
[i80]
[j23]
[i73]
114
Timothy Roughgarden
aka: Tim Roughgarden
[j15]
[c32]
[c24]
[i32]
[i21]
[c6]
[i1]
115
Maxon Rubin-Toles
[c131]
[i138]
116
Emily Ryu
[c135]
[i137]
[i134]
117
Grant Schoenebeck
[c27]
[i31]
[c18]
[i17]
[c5]
[i8]
118
Zachary Schutzman
[c83]
[i83]
[c73]
[c60]
[i61]
[i54]
119
Sikata Bela Sengupta
[i146]
[i145]
[c130]
[i142]
[i136]
[c114]
[i124]
120
Han Shao
[c111]
[i107]
121
Saeed Sharifi-Malvajerdi
[c97]
[c91]
[c87]
[c84]
[c83]
[c82]
[i93]
[i90]
[i89]
[c78]
[c77]
[i86]
[i83]
[i82]
[c69]
[c68]
[i75]
[i69]
[i58]
122
Moshe Shenfeld
[c82]
[c78]
[i69]
123
Mirah Shi
[c136]
[i148]
[c134]
[c124]
[i141]
[i139]
[i134]
[c112]
[i130]
[i128]
124
Amaresh Ankit Siva
[c93]
[i98]
[c86]
[i92]
125
Aleksandra B. Slavkovic
[j25]
126
Aleksandrs Slivkins
[j26]
[c55]
[i48]
127
Adam D. Smith
0001
[c81]
[i72]
[c53]
[i51]
128
Stefano Soatto
[c100]
[i104]
129
Jessica Sorrell
[i146]
[c130]
[i142]
[i136]
[c114]
[i124]
[c104]
[i115]
130
Nathan Srebro
[c81]
[i72]
131
Logan Stapleton
[c88]
[i74]
132
Pierre-Yves Strub
[c43]
[c39]
[i44]
[i28]
133
Buxin Su
[i121]
134
Weijie J. Su
[i121]
[i91]
[i76]
135
Kunal Talwar
[c7]
[c5]
[i8]
[i4]
[i3]
136
Shuai Tang
[c117]
[c115]
[c113]
[i122]
[c102]
[i113]
[i111]
[i106]
[c93]
[i98]
137
Om Thakkar
0001
[c81]
[i72]
[c53]
[i51]
138
Abhradeep Thakurta
[i87]
139
Alexander Tolbert
[c107]
[i101]
140
Jonathan R. Ullman
[j29]
[j26]
[c69]
[c62]
[i65]
[i58]
[j18]
[c55]
[c48]
[c44]
[i49]
[i48]
[j10]
[c37]
[i45]
[i43]
[i36]
[c32]
[c30]
[i34]
[i32]
[j5]
[c20]
[c16]
[i16]
[c12]
[i12]
[i6]
141
Salil P. Vadhan
[c48]
[i49]
142
Giuseppe Vietri
[c132]
[i117]
[c93]
[i98]
[i96]
[c79]
[i70]
143
Rakesh V. Vohra
aka: Rakesh Vohra
[c99]
[c90]
[i94]
[c76]
[i84]
[i81]
[c56]
[i57]
[j14]
[c45]
[i37]
144
Bo Waggoner
[j29]
[j24]
[c67]
[i78]
[c63]
[c62]
[c60]
[i67]
[i65]
[c57]
[i56]
[i54]
145
Chris Waites
[c84]
[i90]
146
Yichen Wang
[c113]
[i113]
147
Yu-Xiang Wang
0003
[c113]
[i113]
[c100]
[i104]
148
Scott Weinstein
[c107]
[i101]
149
Daniel Winograd-Cort
[j19]
150
Blake E. Woodworth
[c81]
[i72]
151
Steven Z. Wu
[c115]
152
Zhiwei Steven Wu
aka: Steven Wu
0001
[c117]
[c113]
[i122]
[c102]
[i113]
[i111]
[i106]
[c93]
[i98]
[i96]
[c88]
[j26]
[c79]
[j24]
[c74]
[c71]
[c67]
[i78]
[i74]
[i70]
[c65]
[c63]
[c60]
[i67]
[i63]
[i59]
[c58]
[c57]
[c56]
[c55]
[i57]
[i56]
[i54]
[i53]
[j17]
[j16]
[j15]
[c54]
[c51]
[c49]
[c46]
[c44]
[i52]
[i48]
[j10]
[c41]
[c37]
[c36]
[c34]
[i45]
[i43]
[i42]
[i41]
[i38]
[c31]
[c24]
[i35]
[i30]
[i26]
[i25]
[i21]
153
Stephan Xie
[c127]
[i108]
154
Yuling Yan
[i121]
155
Grigory Yaroslavtsev
[j16]
[i42]
156
Morteza Zadimoghaddam
[c15]
[i14]
157
Danfeng Zhang
[i87]
158
Hengchu Zhang
[j28]
[i80]
[j23]
[i73]
159
Jiayao Zhang
0001
[i121]
160
Linjun Zhang
[c116]
[i125]
161
Lujing Zhang
[c116]
[i125]
162
Rongting Zhang
0001
[c122]
[i118]
163
Juba Ziani
[c125]
[c119]
[i120]
[c101]
[i109]
[j32]
[i99]
[c85]
[c83]
[c77]
[i86]
[i85]
[i83]
[c72]
[i62]
[c41]
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