Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Kuriwaki, Shiro"'
After an election, should officials release an electronic record of each ballot? The release of ballots could bolster the legitimacy of the result. But it may also facilitate vote revelation, where an analyst unravels the secret ballot by uniquely li
Externí odkaz:
http://arxiv.org/abs/2308.04100
Publikováno v:
Science advances, 10(18) (2024) eadl2524
The United States Census Bureau faces a difficult trade-off between the accuracy of Census statistics and the protection of individual information. We conduct the first independent evaluation of bias and noise induced by the Bureau's two main disclos
Externí odkaz:
http://arxiv.org/abs/2306.07521
Autor:
Kenny, Christopher T., Kuriwaki, Shiro, McCartan, Cory, Rosenman, Evan T. R., Simko, Tyler, Imai, Kosuke
Publikováno v:
Harvard Data Science Review, (Special Issue 2, 2023)
In "Differential Perspectives: Epistemic Disconnects Surrounding the US Census Bureau's Use of Differential Privacy," boyd and Sarathy argue that empirical evaluations of the Census Disclosure Avoidance System (DAS), including our published analysis,
Externí odkaz:
http://arxiv.org/abs/2210.08383
Publikováno v:
Proc. Natl. Acad. Sci. 120(25), 2023
Congressional district lines in many U.S. states are drawn by partisan actors, raising concerns about gerrymandering. To separate the partisan effects of redistricting from the effects of other factors including geography and redistricting rules, we
Externí odkaz:
http://arxiv.org/abs/2208.06968
Autor:
McCartan, Cory, Kenny, Christopher T., Simko, Tyler, Garcia III, George, Wang, Kevin, Wu, Melissa, Kuriwaki, Shiro, Imai, Kosuke
Publikováno v:
Sci Data (2022) 9, 689
This article introduces the 50stateSimulations, a collection of simulated congressional districting plans and underlying code developed by the Algorithm-Assisted Redistricting Methodology (ALARM) Project. The 50stateSimulations allow for the evaluati
Externí odkaz:
http://arxiv.org/abs/2206.10763
Autor:
Bradley, Valerie C., Kuriwaki, Shiro, Isakov, Michael, Sejdinovic, Dino, Meng, Xiao-Li, Flaxman, Seth
Publikováno v:
Nature 600, 695-700 (2021)
Surveys are a crucial tool for understanding public opinion and behavior, and their accuracy depends on maintaining statistical representativeness of their target populations by minimizing biases from all sources. Increasing data size shrinks confide
Externí odkaz:
http://arxiv.org/abs/2106.05818
Autor:
Kenny, Christopher T., Kuriwaki, Shiro, McCartan, Cory, Rosenman, Evan, Simko, Tyler, Imai, Kosuke
Publikováno v:
Science advances, 7(41) (2021) eabk3283
The US Census Bureau plans to protect the privacy of 2020 Census respondents through its Disclosure Avoidance System (DAS), which attempts to achieve differential privacy guarantees by adding noise to the Census microdata. By applying redistricting s
Externí odkaz:
http://arxiv.org/abs/2105.14197
Autor:
Kuriwaki, Shiro, Yamauchi, Soichiro
The comparison of subnational areas is ubiquitous but survey samples of these areas are often biased or prohibitively small. Researchers turn to methods such as multilevel regression and poststratification (MRP) to improve the efficiency of estimates
Externí odkaz:
http://arxiv.org/abs/2105.05829
Autor:
Ansolabehere, Stephen, Kuriwaki, Shiro
Publikováno v:
American Journal of Political Science, 2022 Jan 01. 66(1), 123-139.
Externí odkaz:
https://www.jstor.org/stable/45415742
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