Predicting winner and estimating margin of victory in elections using sampling
From MaRDI portal
Publication:2238579
DOI10.1016/j.artint.2021.103476OpenAlexW3133162735MaRDI QIDQ2238579
Arnab Bhattacharyya, Palash Dey
Publication date: 2 November 2021
Published in: Artificial Intelligence (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.artint.2021.103476
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Lower bounds for sampling algorithms for estimating the average
- The complexity of Kemeny elections
- Kernelization complexity of possible winner and coalitional manipulation problems in voting
- A sharper discrepancy measure for post-election audits
- Voting schemes for which it can be difficult to tell who won the election
- On the evaluation of election outcomes under uncertainty
- Conservative statistical post-election audits
- A combinatorial characterization of the testable graph properties
- Graph limits and parameter testing
- L p Testing and Learning of Discrete Distributions
- Vote Elicitation with Probabilistic Preference Models: Empirical Estimation and Cost Tradeoffs
- Divergence measures based on the Shannon entropy
- Asymptotic Minimax Character of the Sample Distribution Function and of the Classical Multinomial Estimator
- Sampling lower bounds via information theory
- Eliciting Single-Peaked Preferences Using Comparison Queries
- How Hard Is Bribery in Elections?
- Exact analysis of Dodgson elections
- Sampling algorithms
- Handbook of Computational Social Choice
- On Information and Sufficiency
This page was built for publication: Predicting winner and estimating margin of victory in elections using sampling