Ryan Rogers

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 24

Top Topics

Differentially Private

Differential Privacy

Top Venues

Publications

Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Steven Wu
Fully-Adaptive Composition in Differential Privacy. ICML (2023)
Ryan Rogers, Gennady Samorodnitsky, Zhiwei Steven Wu, Aaditya Ramdas
Adaptive Privacy Composition for Accuracy-first Mechanisms. CoRR (2023)
Ryan Rogers
A Unifying Privacy Analysis Framework for Unknown Domain Algorithms in Differential Privacy. CoRR (2023)
Justin Whitehouse, Zhiwei Steven Wu, Aaditya Ramdas, Ryan Rogers
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints. CoRR (2022)
Rina Friedberg, Ryan Rogers
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach. AFCP (2022)
Justin Whitehouse, Aaditya Ramdas, Ryan Rogers, Zhiwei Steven Wu
Fully Adaptive Composition in Differential Privacy. CoRR (2022)
Adrian Rivera Cardoso, Ryan Rogers
Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown. AISTATS (2022)
Adrian Rivera Cardoso, Ryan Rogers
Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown. CoRR (2021)
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)
Mark Cesar, Ryan Rogers
Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics. ALT (2021)
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 (2020)
Mark Cesar, Ryan Rogers
Unifying Privacy Loss Composition for Data Analytics. CoRR (2020)
Jinshuo Dong, David Durfee, Ryan Rogers
Optimal Differential Privacy Composition for Exponential Mechanisms. ICML (2020)
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 (2020)
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)
Jinshuo Dong, David Durfee, Ryan Rogers
Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity. CoRR (2019)
Ryan Rogers, Aaron Roth, Adam D. Smith, Nathan Srebro, Om Thakkar, Blake E. Woodworth
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis. CoRR (2019)
Marco Gaboardi, Ryan Rogers, Or Sheffet
Locally Private Mean Estimation: $Z$-test and Tight Confidence Intervals. AISTATS (2019)
David Durfee, Ryan Rogers
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition. CoRR (2019)
Marco Gaboardi, Ryan Rogers
Local Private Hypothesis Testing: Chi-Square Tests. ICML (2018)
Marco Gaboardi, Ryan Rogers, Or Sheffet
Locally Private Mean Estimation: Z-test and Tight Confidence Intervals. CoRR (2018)
Sampath Kannan, Jamie Morgenstern, Ryan Rogers, Aaron Roth
Private Pareto Optimal Exchange. ACM Trans. Economics and Comput. 6 (3-4) (2018)
Ryan Rogers, Daniel Kifer
A New Class of Private Chi-Square Hypothesis Tests. AISTATS (2017)
Daniel Kifer, Ryan Rogers
A New Class of Private Chi-Square Tests. CoRR (2016)