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ORCIDRyan Rogers 0002
Person information
- affiliation: LinkedIn, Applied Research
- affiliation (former): University of Pennsylvania, Department of Mathematics, Philadelphia, PA, USA
Other persons with the same name
- Ryan Rogers 0001 — Marist College, Poughkeepsie, USA
- Ryan Rogers 0003 — Apple Inc., ML Privacy Team
- Ryan Rogers 0004 — McMaster University, Department of Mechanical Engineering, Canada
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2020 – today
- 2024
[i25]Saikrishna Badrinarayanan, Osonde Osoba, Miao Cheng, Ryan Rogers, Sakshi Jain, Rahul Tandra, Natesh S. Pillai:
Privacy-Preserving Race/Ethnicity Estimation for Algorithmic Bias Measurement in the U.S. CoRR abs/2409.04652 (2024)- 2023
- [c21]Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Steven Wu:
Fully-Adaptive Composition in Differential Privacy. ICML 2023: 36990-37007 - [c20]Ryan M. Rogers, Gennady Samorodnitsky, Zhiwei Steven Wu, Aaditya Ramdas:
Adaptive Privacy Composition for Accuracy-first Mechanisms. NeurIPS 2023 - [i24]Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath
, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang:
Challenges towards the Next Frontier in Privacy. CoRR abs/2304.06929 (2023) - [i23]Ryan Rogers, Gennady Samorodnitsky, Zhiwei Steven Wu, Aaditya Ramdas:
Adaptive Privacy Composition for Accuracy-first Mechanisms. CoRR abs/2306.13824 (2023) - [i22]Ryan Rogers:
A Unifying Privacy Analysis Framework for Unknown Domain Algorithms in Differential Privacy. CoRR abs/2309.09170 (2023) - 2022
- [c19]Rina Friedberg, Ryan Rogers:
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach. AFCP 2022: 23-66 - [c18]Adrian Rivera Cardoso, Ryan Rogers:
Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown. AISTATS 2022: 2397-2419 - [c17]Justin Whitehouse, Aaditya Ramdas, Zhiwei Steven Wu, Ryan M. Rogers:
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints. NeurIPS 2022 - [i21]Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Zhiwei Steven Wu:
Fully Adaptive Composition in Differential Privacy. CoRR abs/2203.05481 (2022) - [i20]Justin Whitehouse, Zhiwei Steven Wu, Aaditya Ramdas, Ryan Rogers:
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints. CoRR abs/2206.07234 (2022) - 2021
- [j3]Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad:
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale. J. Priv. Confidentiality 11(3) (2021) - [c16]Mark Cesar, Ryan Rogers:
Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics. ALT 2021: 421-457 - [i19]Adrian Rivera Cardoso, Ryan Rogers:
Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown. CoRR abs/2103.16787 (2021) - 2020
- [c15]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 - [c14]Jinshuo Dong, David Durfee, Ryan Rogers:
Optimal Differential Privacy Composition for Exponential Mechanisms. ICML 2020: 2597-2606 - [i18]Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad:
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale. CoRR abs/2002.05839 (2020) - [i17]Mark Cesar, Ryan Rogers:
Unifying Privacy Loss Composition for Data Analytics. CoRR abs/2004.07223 (2020) - [i16]Ryan Rogers, Adrian Rivera Cardoso, Koray Mancuhan, Akash Kaura, Nikhil Gahlawat, Neha Jain, Paul Ko, Parvez Ahammad:
A Members First Approach to Enabling LinkedIn's Labor Market Insights at Scale. CoRR abs/2010.13981 (2020)
2010 – 2019
- 2019
- [c13]Marco Gaboardi, Ryan Rogers, Or Sheffet:
Locally Private Mean Estimation: $Z$-test and Tight Confidence Intervals. AISTATS 2019: 2545-2554 - [c12]David Durfee, Ryan M. Rogers:
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition. NeurIPS 2019: 3527-3537 - [i15]David Durfee, Ryan Rogers:
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition. CoRR abs/1905.04273 (2019) - [i14]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) - [i13]Jinshuo Dong, David Durfee, Ryan Rogers:
Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity. CoRR abs/1909.13830 (2019) - 2018
- [j2]Sampath Kannan, Jamie Morgenstern, Ryan Rogers, Aaron Roth:
Private Pareto Optimal Exchange. ACM Trans. Economics and Comput. 6(3-4): 12:1-12:25 (2018) - [c11]Marco Gaboardi, Ryan Rogers:
Local Private Hypothesis Testing: Chi-Square Tests. ICML 2018: 1612-1621 - [i12]Marco Gaboardi, Ryan Rogers, Or Sheffet:
Locally Private Mean Estimation: Z-test and Tight Confidence Intervals. CoRR abs/1810.08054 (2018) - 2017
- [c10]Ryan Rogers, Daniel Kifer:
A New Class of Private Chi-Square Hypothesis Tests. AISTATS 2017: 991-1000 - [c9]Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan:
A Decomposition of Forecast Error in Prediction Markets. NIPS 2017: 4371-4380 - [i11]Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan:
A Decomposition of Forecast Error in Prediction Markets. CoRR abs/1702.07810 (2017) - [i10]Marco Gaboardi, Ryan M. Rogers:
Local Private Hypothesis Testing: Chi-Square Tests. CoRR abs/1709.07155 (2017) - 2016
- [j1]Justin Hsu, Jamie Morgenstern, Ryan M. Rogers, Aaron Roth, Rakesh Vohra:
Do prices coordinate markets? SIGecom Exch. 15(1): 84-88 (2016) - [c8]Ryan M. Rogers, Aaron Roth, Adam D. Smith, Om Thakkar:
Max-Information, Differential Privacy, and Post-selection Hypothesis Testing. FOCS 2016: 487-494 - [c7]Marco Gaboardi, Hyun-Woo Lim, Ryan M. Rogers, Salil P. Vadhan:
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing. ICML 2016: 2111-2120 - [c6]Shahin Jabbari, Ryan M. Rogers, Aaron Roth, Zhiwei Steven Wu:
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs. NIPS 2016: 1570-1578 - [c5]Ryan M. Rogers, Salil P. Vadhan, Aaron Roth, Jonathan R. Ullman:
Privacy Odometers and Filters: Pay-as-you-Go Composition. NIPS 2016: 1921-1929 - [c4]Justin Hsu, Jamie Morgenstern, Ryan M. Rogers, Aaron Roth, Rakesh Vohra:
Do prices coordinate markets? STOC 2016: 440-453 - [i9]Marco Gaboardi, Hyun-Woo Lim, Ryan M. Rogers, Salil P. Vadhan:
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing. CoRR abs/1602.03090 (2016) - [i8]Ryan M. Rogers, Aaron Roth, Adam D. Smith, Om Thakkar:
Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing. CoRR abs/1604.03924 (2016) - [i7]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) - [i6]Daniel Kifer, Ryan Rogers:
A New Class of Private Chi-Square Tests. CoRR abs/1610.07662 (2016) - 2015
- [c3]Sampath Kannan, Jamie Morgenstern, Ryan M. Rogers, Aaron Roth:
Private Pareto Optimal Exchange. EC 2015: 261-278 - [c2]Ryan M. Rogers, Aaron Roth, Jonathan R. Ullman, Zhiwei Steven Wu:
Inducing Approximately Optimal Flow Using Truthful Mediators. EC 2015: 471-488 - [i5]Ryan M. Rogers, Aaron Roth, Jonathan R. Ullman, Zhiwei Steven Wu:
Inducing Approximately Optimal Flow Using Truthful Mediators. CoRR abs/1502.04019 (2015) - [i4]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) - [i3]Justin Hsu, Jamie Morgenstern, Ryan M. Rogers, Aaron Roth, Rakesh Vohra:
Do Prices Coordinate Markets? CoRR abs/1511.00925 (2015) - [i2]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
- [c1]Ryan M. Rogers, Aaron Roth:
Asymptotically truthful equilibrium selection in large congestion games. EC 2014: 771-782 - [i1]Sampath Kannan, Jamie Morgenstern, Ryan M. Rogers, Aaron Roth:
Private Pareto Optimal Exchange. CoRR abs/1407.2641 (2014)
Coauthor Index
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