Demo Data from EDBT 2026 / reviewers in the wild / expert
M. Remzi Sanver
dblp:62/8448
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › social choice
computational social choice |
0.6 | 1 | 2022 | Approval with Runoff · IJCAI 2022 |
Algorithmic game theory and mechanism design › social choice › computational social choice
axiomatic analysis |
0.2 | 1 | 2022 | Approval with Runoff · IJCAI 2022 |
Algorithmic game theory and mechanism design › social choice › restricted preference domains
single-peaked preferences |
0.2 | 1 | 2022 | Approval with Runoff · IJCAI 2022 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Approval with RunoffabstractWe define a family of runoff rules that work as follows: voters cast approval ballots over candidates; two finalists are selected; and the winner is decided by majority. With approval-type ballots, there are various ways to select the finalists. We leverage known approval-based committee rules and study the obtained runoff rules from an axiomatic point of view. Then we analyze the outcome of these rules on single-peaked profiles, and on real data. Theo Delemazure, Jérôme Lang, Jean-François Laslier, M. Remzi Sanver |
IJCAI | 4 |