Demo Data from EDBT 2026 / reviewers in the wild / expert
Ilan Yaniv
dblp:143/9392
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0003-4960-4975ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1
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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › mechanism design › auction design
ad auction |
0.2 | 1 | 2014 | An experimental evaluation of bidders' behavior in ad auctions · WWW 2014 |
Algorithmic game theory and mechanism design › mechanism design › auction design › ad auction › position auction
generalized second price auction |
0.2 | 1 | 2014 | An experimental evaluation of bidders' behavior in ad auctions · WWW 2014 |
Algorithmic game theory and mechanism design › mechanism design › truthful mechanism
VCG mechanism |
0.2 | 1 | 2014 | An experimental evaluation of bidders' behavior in ad auctions · WWW 2014 |
Algorithmic game theory and mechanism design
social welfare |
0.1 | 1 | 2014 | An experimental evaluation of bidders' behavior in ad auctions · WWW 2014 |
Methods — techniques the papers use, named apart from their topics
controlled experiment · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | An experimental evaluation of bidders' behavior in ad auctionsabstractWe performed controlled experiments of human participants in a continuous sequence of ad auctions, similar to those used by Internet companies. The goal of the research was to understand users' strategies in making bids. We studied the behavior under two auction types: (1) the Generalized Second-Price (GSP) auction and (2) the Vickrey--Clarke--Groves (VCG) payment rule, and manipulated also the participants' knowledge conditions: (1) explicitly given valuations and (2) payoff information from which valuations could be deduced. We found several interesting behaviors, among them are: No convergence to equilibrium was detected; moreover the frequency with which participants modified their bids increased with time. We can detect explicit "better-response" behavior rather than just mixed bidding. While bidders in GSP auctions do strategically shade their bids, they tend to bid higher than theoretically predicted by the standard VCG-like equilibrium of GSP. Bidders who are not explicitly given their valuations but can only deduce them from their gains behave a little less "precisely" than those with such explicit knowledge, but mostly during an initial learning phase. VCG and GSP yield approximately the same (high) social welfare, but GSP tends to give higher revenue. Gali Noti, Noam Nisan, Ilan Yaniv |
WWW | 3 |