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Demo Data from EDBT 2026 / reviewers in the wild / expert

Jinhuan Li

dblp:223/1401 · DBLP profile ↗
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1ranked-venue papers
0as 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 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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 paradigms · 87% Trustworthy machine learning · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Learning paradigms
multi-label classification		 0.812024
Boosting Single Positive Multi-label Classification with Generalized Robust Loss · IJCAI 2024
Machine learning › Learning paradigms › multi-label classification
single positive multi-label learning		 0.812024
Boosting Single Positive Multi-label Classification with Generalized Robust Loss · IJCAI 2024
Machine learning › Trustworthy machine learning › robustness › robust learning
robust loss functions		 0.212024
Boosting Single Positive Multi-label Classification with Generalized Robust Loss · IJCAI 2024

Methods — techniques the papers use, named apart from their topics

robust loss · 0.8
YearPublicationVenuePosition
2024 Boosting Single Positive Multi-label Classification with Generalized Robust Loss
Xinyang Dai, Jinhuan Li, Weiyu Sun, Tinghe Zhang
 IJCAI4