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ORCIDPriyanka Nanayakkara
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2020 – today
- 2024
[c5]Priyanka Nanayakkara, Hyeok Kim, Yifan Wu, Ali Sarvghad, Narges Mahyar, Gerome Miklau, Jessica Hullman:
Measure-Observe-Remeasure: An Interactive Paradigm for Differentially-Private Exploratory Analysis. SP 2024: 1047-1064- [i9]Priyanka Nanayakkara, Hyeok Kim, Yifan Wu, Ali Sarvghad, Narges Mahyar, Gerome Miklau, Jessica Hullman:
Measure-Observe-Remeasure: An Interactive Paradigm for Differentially-Private Exploratory Analysis. CoRR abs/2406.01964 (2024) - [i8]Mary Anne Smart, Priyanka Nanayakkara, Rachel Cummings, Gabriel Kaptchuk, Elissa M. Redmiles:
Models Matter: Setting Accurate Privacy Expectations for Local and Central Differential Privacy. CoRR abs/2408.08475 (2024) - [i7]Priyanka Nanayakkara, Jessica Hullman:
What to Consider When Considering Differential Privacy for Policy. CoRR abs/2409.11680 (2024) - 2023
- [j2]Priyanka Nanayakkara
, Jessica Hullman:
What's Driving Conflicts Around Differential Privacy for the U.S. Census. IEEE Secur. Priv. 21(5): 33-42 (2023) - [c4]Priyanka Nanayakkara, Mary Anne Smart, Rachel Cummings, Gabriel Kaptchuk, Elissa M. Redmiles:
What Are the Chances? Explaining the Epsilon Parameter in Differential Privacy. USENIX Security Symposium 2023: 1613-1630 - [i6]Priyanka Nanayakkara, Mary Anne Smart, Rachel Cummings, Gabriel Kaptchuk, Elissa M. Redmiles:
What Are the Chances? Explaining the Epsilon Parameter in Differential Privacy. CoRR abs/2303.00738 (2023) - [i5]Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan:
REFORMS: Reporting Standards for Machine Learning Based Science. CoRR abs/2308.07832 (2023) - 2022
- [j1]Priyanka Nanayakkara, Johes Bater, Xi He, Jessica Hullman, Jennie Rogers:
Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases. Proc. Priv. Enhancing Technol. 2022(2): 601-618 (2022) - [c3]Jessica Hullman, Sayash Kapoor, Priyanka Nanayakkara, Andrew Gelman, Arvind Narayanan:
The Worst of Both Worlds: A Comparative Analysis of Errors in Learning from Data in Psychology and Machine Learning. AIES 2022: 335-348 - [c2]David Liu, Priyanka Nanayakkara, Sarah Ariyan Sakha, Grace Abuhamad, Su Lin Blodgett, Nicholas Diakopoulos, Jessica R. Hullman, Tina Eliassi-Rad:
Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews. AIES 2022: 424-435 - [i4]Priyanka Nanayakkara, Johes Bater, Xi He, Jessica Hullman, Jennie Rogers:
Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases. CoRR abs/2201.05964 (2022) - [i3]Jessica Hullman, Sayash Kapoor, Priyanka Nanayakkara, Andrew Gelman, Arvind Narayanan:
The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning. CoRR abs/2203.06498 (2022) - 2021
- [c1]Priyanka Nanayakkara, Jessica Hullman, Nicholas Diakopoulos:
Unpacking the Expressed Consequences of AI Research in Broader Impact Statements. AIES 2021: 795-806 - [i2]Priyanka Nanayakkara, Jessica Hullman, Nicholas Diakopoulos:
Unpacking the Expressed Consequences of AI Research in Broader Impact Statements. CoRR abs/2105.04760 (2021) - 2020
- [i1]Priyanka Nanayakkara, Nicholas Diakopoulos, Jessica Hullman:
Anticipatory Ethics and the Role of Uncertainty. CoRR abs/2011.13170 (2020)
Coauthor Index
aka: Jessica R. Hullman
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