VLDB 2026 Research / reviewers in the wild / expert
Krzysztof Wojtas
dblp:95/1793
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
1 paper |
Algorithmic game theory and mechanism design · 54% Computational complexity · 46% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational complexity › counting complexity
#p-completeness |
0.1 | 1 | 2012 | Possible Winners in Noisy Elections · AAAI 2012 |
Algorithmic game theory and mechanism design › social choice
computational social choice |
0.1 | 1 | 2012 | Possible Winners in Noisy Elections · AAAI 2012 |
Computational complexity
counting complexity |
0.1 | 1 | 2012 | Possible Winners in Noisy Elections · AAAI 2012 |
Algorithmic game theory and mechanism design › social choice › computational social choice
election control |
0.1 | 1 | 2012 | Possible Winners in Noisy Elections · AAAI 2012 |
Algorithmic game theory and mechanism design › social choice › computational social choice
voting rules |
0.0 | 1 | 2012 | Possible Winners in Noisy Elections · AAAI 2012 |
Methods — techniques the papers use, named apart from their topics
polynomial-time algorithm · 0.1hardness reduction · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Possible Winners in Noisy ElectionsabstractWe consider the problem of predicting winners in elections given complete knowledge about all possible candidates, all possible voters (together with their preferences), but in the case where it is uncertain either which candidates exactly register for the election or which voters cast their votes. Under reasonable assumptions our problems reduce to counting variants of election control problems. We either give polynomial-time algorithms or prove #P-completeness results for counting variants of control by adding/deleting candidates/voters for Plurality, k-Approval, Approval, Condorcet, and Maximin voting rules. Krzysztof Wojtas, Piotr Faliszewski |
AAAI | 1 |