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

Hai-Jian Ke

dblp:392/9786 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 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
2 papers
Efficient and distributed learning · 50% Learning paradigms · 22% Motion planning and robot control · 22%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Efficient and distributed learning
active learning		 1.012026
Evidence Conflict Sampling for Open-set Active Learning · Int. J. Comput. Vis. 2026
Machine learning › Learning paradigms
continual learning		 1.012026
Sparse Orthogonal Parameters Tuning for Continual Learning · Int. J. Comput. Vis. 2026
Machine learning › Efficient and distributed learning › active learning › active learning for classification
open-set active learning		 1.012026
Evidence Conflict Sampling for Open-set Active Learning · Int. J. Comput. Vis. 2026
Robotics › Motion planning and robot control
parameter tuning		 1.012026
Sparse Orthogonal Parameters Tuning for Continual Learning · Int. J. Comput. Vis. 2026
Machine learning › Efficient and distributed learning
parameter-efficient fine-tuning		 0.312026
Sparse Orthogonal Parameters Tuning for Continual Learning · Int. J. Comput. Vis. 2026
Machine learning › Trustworthy machine learning
uncertainty estimation		 0.312026
Evidence Conflict Sampling for Open-set Active Learning · Int. J. Comput. Vis. 2026

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

sparse orthogonal parameters · 1.0parameter tuning · 1.0evidence conflict sampling · 1.0active learning · 1.0
YearPublicationVenuePosition
2026 Sparse Orthogonal Parameters Tuning for Continual Learning
Kun-Peng Ning, Hai-Jian Ke, Jia-Yu Yao, Yonghong Tian 0001, Li Yuan 0007
 Int. J. Comput. Vis.2
2026 Evidence Conflict Sampling for Open-set Active Learning
Kun-Peng Ning, Hai-Jian Ke, Jia-Yu Yao, Yonghong Tian 0001, Li Yuan 0007
 Int. J. Comput. Vis.2