Demo Data from EDBT 2026 / reviewers in the wild / expert
Aditya V. Sunderam
dblp:68/3795
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorTheory of computation · 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 · 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 |
0.0 | 1 | 2003 | Preference elicitation in proxied multiattribute auctions · EC 2003 |
Algorithmic game theory and mechanism design › mechanism design › auction design
multi-attribute auction |
0.0 | 1 | 2003 | Preference elicitation in proxied multiattribute auctions · EC 2003 |
Algorithmic game theory and mechanism design
preference elicitation |
0.0 | 1 | 2003 | Preference elicitation in proxied multiattribute auctions · EC 2003 |
Algorithmic game theory and mechanism design › auction theory › bidding strategy
proxy bidding |
0.0 | 1 | 2003 | Preference elicitation in proxied multiattribute auctions · EC 2003 |
Methods — techniques the papers use, named apart from their topics
proxy bidding agents · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Preference elicitation in proxied multiattribute auctionsabstractWe consider the problem of minimizing preference elicitation in efficient multiattribute auctions, that support dynamic negotiation over non-price based attributes such as quality, time-of-delivery, and processor speed. We introduce asynchronous price-based multiattribute auctions, with proxy bidding agents that sit between the auctioneer and the participants. Empirical results demonstrate the preference elicitation savings that are provided with minimal price spaces, asynchronous updates, and proxy agents. Aditya V. Sunderam, David C. Parkes |
EC | 1 |