Demo Data from VLDB 2026 / reviewers in the wild / expert
Richard Faltings
dblp:410/3267
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0002-2535-7976ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Theory of computation · 1 · 1 first-author · 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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › market design
matching markets |
0.9 | 1 | 2025 | Pricing the Right to Renege in Search Markets: Evidence from Trucking · EC 2025 |
Algorithmic game theory and mechanism design
pricing |
0.9 | 1 | 2025 | Pricing the Right to Renege in Search Markets: Evidence from Trucking · EC 2025 |
Methods — techniques the papers use, named apart from their topics
empirical analysis · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Pricing the Right to Renege in Search Markets: Evidence from TruckingabstractIn many decentralized markets, participants search sequentially over alternatives without knowing future matching opportunities, which can lead to suboptimal outcomes. Intuitively, efficiency can be improved by an explicit right to renege, preserving one party's option value to keep searching for better opportunities while the other sacrifices theirs for the duration of the agreement. The question is then: how should this right be priced? Richard Faltings |
EC | 1 |