Demo Data from EDBT 2026 / reviewers in the wild / expert
Stephen Gross
dblp:195/8210
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · unresolved
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 · 87% Computational complexity · 13% |
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 › mechanism design › algorithmic mechanism design
randomized mechanism |
0.3 | 1 | 2017 | Vote Until Two of You Agree: Mechanisms with Small Distortion and Sample Complexity · AAAI 2017 |
Algorithmic game theory and mechanism design
social choice |
0.3 | 1 | 2017 | Vote Until Two of You Agree: Mechanisms with Small Distortion and Sample Complexity · AAAI 2017 |
Computational complexity › learning theory
sample complexity |
0.1 | 1 | 2017 | Vote Until Two of You Agree: Mechanisms with Small Distortion and Sample Complexity · AAAI 2017 |
Methods — techniques the papers use, named apart from their topics
randomized mechanism design · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Vote Until Two of You Agree: Mechanisms with Small Distortion and Sample ComplexityabstractTo design social choice mechanisms with desirable utility properties, normative properties, and low sample complexity, we propose a new randomized mechanism called 2-Agree. This mechanism asks random voters for their top alternatives until at least two voters agree, at which point it selects that alternative as the winner. We prove that, despite its simplicity and low sample complexity, 2-Agree achieves almost optimal distortion on a metric space when the number of alternatives is not large, and satisfies anonymity, neutrality, ex-post Pareto efficiency, very strong SD-participation, and is approximately truthful. We further show that 2-Agree works well for larger number of alternatives with decisive agents. Stephen Gross, Elliot Anshelevich, Lirong Xia |
AAAI | 1 |