Demo Data from EDBT 2026 / reviewers in the wild / expert
Zhaoxiang Jing
dblp:18/10551
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Applied, interdisciplinary, general and emerging computing · 1
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 |
Kernel, tree and ensemble methods · 65% Learning theory · 35% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Kernel, tree and ensemble methods › ensemble learning
boosting |
0.3 | 2 | 2012 | Further results on the margin explanation of boosting: new algorithm and experiments · Sci. China Inf. Sci. 2012 A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin · J. Mach. Learn. Res. 2011 |
Machine learning › Learning theory › generalization bounds
margin theory |
0.1 | 1 | 2012 | Further results on the margin explanation of boosting: new algorithm and experiments · Sci. China Inf. Sci. 2012 |
Methods — techniques the papers use, named apart from their topics
boosting · 0.1equilibrium margin · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Further results on the margin explanation of boosting: new algorithm and experiments
Liwei Wang 0001, Xiaocheng Deng, Zhaoxiang Jing, Jufu Feng |
Sci. China Inf. Sci. | 3 |
| 2011 | A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin
Liwei Wang 0001, Masashi Sugiyama, Zhaoxiang Jing, Zhi-Hua Zhou, Jufu Feng |
J. Mach. Learn. Res. | 3 |