Demo Data from EDBT 2026 / reviewers in the wild / expert
Maytal Bremer
dblp:195/8213
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 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.
| Artificial intelligence
1 paper |
Planning, search and constraint satisfaction · 50% Efficient and distributed learning · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Efficient and distributed learning › federated learning
incentive mechanism |
0.3 | 1 | 2017 | Nurturing Group-Beneficial Information-Gathering Behaviors Through Above-Threshold Criteria Setting · AAAI 2017 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning under uncertainty
information gathering |
0.3 | 1 | 2017 | Nurturing Group-Beneficial Information-Gathering Behaviors Through Above-Threshold Criteria Setting · AAAI 2017 |
Methods — techniques the papers use, named apart from their topics
mechanism design · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Nurturing Group-Beneficial Information-Gathering Behaviors Through Above-Threshold Criteria Setting
Igor Rochlin, David Sarne, Maytal Bremer, Ben Grynhaus |
AAAI | 3 |