Demo Data from EDBT 2026 / reviewers in the wild / expert
Irene Kameni
dblp:276/7524 · also Irene Raissa Kameni
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—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 |
Learning theory · 67% Transfer learning and domain adaptation · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Learning theory › statistical estimation
estimation error bounds |
0.5 | 1 | 2021 | Theoretical bounds on estimation error for meta-learning · ICLR 2021 |
Machine learning › Transfer learning and domain adaptation
meta-learning |
0.5 | 1 | 2021 | Theoretical bounds on estimation error for meta-learning · ICLR 2021 |
Machine learning › Learning theory
meta-learning theory |
0.5 | 1 | 2021 | Theoretical bounds on estimation error for meta-learning · ICLR 2021 |
Methods — techniques the papers use, named apart from their topics
statistical learning theory · 0.5generalization bounds · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Theoretical bounds on estimation error for meta-learning
James Lucas, Mengye Ren, Irene Kameni, Toniann Pitassi, Richard S. Zemel |
ICLR | 3 |