RAIRE: Risk-Limiting Audits for IRV Elections
March 20, 2019 Β· Declared Dead Β· + Add venue
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Michelle Blom, Peter J. Stuckey, Vanessa Teague
arXiv ID
1903.08804
Category
cs.DS: Data Structures & Algorithms
Citations
14
Last Checked
3 months ago
Abstract
Risk-limiting post election audits guarantee a high probability of correcting incorrect election results, independent of why the result was incorrect. Ballot-polling audits select ballots at random and interpret those ballots as evidence for and against the reported result, continuing this process until either they support the recorded result, or they fall back to a full manual recount. For elections with digitised scanning and counting of ballots, a comparison audit compares randomly selected digital ballots with their paper versions. Discrepancies are referred to as errors, and are used to build evidence against or in support of the recorded result. Risk-limiting audits for first-past-the-post elections are well understood, and used in some US elections. We define a number of approaches to ballot-polling and comparison risk-limiting audits for Instant Runoff Voting (IRV) elections. We show that for almost all real elections we found, we can perform a risk-limiting audit by looking at only a small fraction of the total ballots (assuming no errors were made in the tallying and distribution of votes).
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
π
π
The Cartographer
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
π
π
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted