Demo Data from VLDB 2026 / reviewers in the wild / expert
Yaowen Kuang
dblp:422/2356
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0002-4291-6407ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 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 |
Efficient and distributed learning · 67% Trustworthy machine 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 › Trustworthy machine learning
machine unlearning |
1.0 | 1 | 2026 | DeepUL: Deep Unlearning via Model Sparsity · WWW 2026 |
Machine learning › Efficient and distributed learning
model compression |
1.0 | 1 | 2026 | DeepUL: Deep Unlearning via Model Sparsity · WWW 2026 |
Machine learning › Efficient and distributed learning › model compression › sparsity
model sparsification |
1.0 | 1 | 2026 | DeepUL: Deep Unlearning via Model Sparsity · WWW 2026 |
Methods — techniques the papers use, named apart from their topics
pruning · 1.0model sparsity · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | DeepUL: Deep Unlearning via Model Sparsity
Zhigao Zheng 0001, Yaowen Kuang, Tao Wang 0037, Yahong Chen, Shihong Yao, Hao Huang 0001 |
WWW | 3 |