Demo Data from VLDB 2026 / reviewers in the wild / expert
Paul Daoudi
dblp:347/7716
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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.
| Artificial intelligence
1 paper |
Transfer learning and domain adaptation · 67% Reinforcement learning · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Transfer learning and domain adaptation
few-shot learning |
0.8 | 1 | 2024 | A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning · IJCAI 2024 |
Machine learning › Transfer learning and domain adaptation › few-shot learning
few-shot transfer |
0.8 | 1 | 2024 | A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning · IJCAI 2024 |
Machine learning › Reinforcement learning › robust reinforcement learning
off-dynamics reinforcement learning |
0.8 | 1 | 2024 | A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning · IJCAI 2024 |
Methods — techniques the papers use, named apart from their topics
conservative policy learning · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning
Paul Daoudi, Christophe Prieur 0001, Bogdan Robu, Merwan Barlier, Ludovic Dos Santos |
IJCAI | 1 |