EDBT 2026 Demo / reviewers in the wild / expert
Yiqi Yang
dblp:275/2192
· DBLP profile ↗
2ranked-venue papers
2as first author
2since 2021 · last 2025
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-author · 2 since 2021Theory of computation · 1 · 1 first-author · 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.
| Theoretical computer science
1 paper |
Algorithmic game theory and mechanism design · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Recommender systems · 100% | |
| Artificial intelligence
1 paper |
Kernel, tree and ensemble methods · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Recommender systems
choice modeling |
0.9 | 1 | 2025 | Reproducing Kernel Hilbert Space Choice Model · EC 2025 |
Algorithmic game theory and mechanism design › decision theory
discrete choice model |
0.9 | 1 | 2025 | Reproducing Kernel Hilbert Space Choice Model · EC 2025 |
Algorithmic game theory and mechanism design › decision theory
random utility model |
0.9 | 1 | 2025 | Reproducing Kernel Hilbert Space Choice Model · EC 2025 |
Machine learning › Kernel, tree and ensemble methods
kernel methods |
0.3 | 1 | 2025 | Reproducing Kernel Hilbert Space Choice Model · EC 2025 |
Methods — techniques the papers use, named apart from their topics
reproducing kernel hilbert space · 2.6discrete choice modeling · 2.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Reproducing Kernel Hilbert Space Choice ModelabstractDiscrete choice models are fundamental for predicting how individuals select among alternatives based on their preferences and the attributes of the options. Traditional Random Utility Models assume stochastic rationality, often failing to capture context-dependent behavior—where the presence of certain alternatives alters the perceived utility of others. Yiqi Yang, Rui Gao 0001, Shuang Li 0002 |
EC | 1 |
| 2022 | SDCN: A Species-Disease Hybrid Convolutional Neural Network for Plant Disease Recognition
Yiqi Yang |
ICANN (4) | 1 |