Demo Data from EDBT 2026 / reviewers in the wild / expert
Jordan Alexander
dblp:236/4810
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 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 |
Reinforcement learning · 67% Knowledge representation and reasoning · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Reinforcement learning › imitation learning
inverse reinforcement learning |
0.4 | 1 | 2019 | Preferences Implicit in the State of the World · ICLR (Poster) 2019 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › nonmonotonic reasoning › preference handling › preference reasoning
preference inference |
0.4 | 1 | 2019 | Preferences Implicit in the State of the World · ICLR (Poster) 2019 |
Machine learning › Reinforcement learning
reward design |
0.4 | 1 | 2019 | Preferences Implicit in the State of the World · ICLR (Poster) 2019 |
Methods — techniques the papers use, named apart from their topics
reinforcement learning · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Preferences Implicit in the State of the World
Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca D. Dragan |
ICLR (Poster) | 3 |