Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
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
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
Journal Articles
- 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)- 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) - 2016
- [j1]Justin Hsu, Jamie Morgenstern, Ryan M. Rogers, Aaron Roth, Rakesh Vohra:
Do prices coordinate markets? SIGecom Exch. 15(1): 84-88 (2016)
Conference and Workshop Papers
- 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 - 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 - 2021
- [c16]Mark Cesar, Ryan Rogers:
Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics. ALT 2021: 421-457 - 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 - 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 - 2018
- [c11]Marco Gaboardi, Ryan Rogers:
Local Private Hypothesis Testing: Chi-Square Tests. ICML 2018: 1612-1621 - 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 - 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 - 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 - 2014
- [c1]Ryan M. Rogers, Aaron Roth:
Asymptotically truthful equilibrium selection in large congestion games. EC 2014: 771-782
Informal and Other Publications
- 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
- [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
- [i19]Adrian Rivera Cardoso, Ryan Rogers:
Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown. CoRR abs/2103.16787 (2021) - 2020
- [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) - 2019
- [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
- [i12]Marco Gaboardi, Ryan Rogers, Or Sheffet:
Locally Private Mean Estimation: Z-test and Tight Confidence Intervals. CoRR abs/1810.08054 (2018) - 2017
- [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
- [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
- [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
- [i1]Sampath Kannan, Jamie Morgenstern, Ryan M. Rogers, Aaron Roth:
Private Pareto Optimal Exchange. CoRR abs/1407.2641 (2014)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-04-25 01:22 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
