VLDB 2026 Research / reviewers in the wild / expert
Katherine Shu
dblp:321/1060
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 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 |
Reinforcement learning · 100% |
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
exploration |
0.6 | 1 | 2022 | Reward Uncertainty for Exploration in Preference-based Reinforcement Learning · ICLR 2022 |
Machine learning › Reinforcement learning › reinforcement learning from human feedback
preference-based reinforcement learning |
0.6 | 1 | 2022 | Reward Uncertainty for Exploration in Preference-based Reinforcement Learning · ICLR 2022 |
Machine learning › Reinforcement learning
reward uncertainty |
0.6 | 1 | 2022 | Reward Uncertainty for Exploration in Preference-based Reinforcement Learning · ICLR 2022 |
Methods — techniques the papers use, named apart from their topics
reward uncertainty estimation · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Reward Uncertainty for Exploration in Preference-based Reinforcement Learning
Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel |
ICLR | 2 |