Demo Data from EDBT 2026 / reviewers in the wild / expert
Gokul Ram Subramani
dblp:412/8333
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—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 |
Optimization for machine learning · 67% Learning paradigms · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Learning paradigms
multi-task learning |
0.9 | 1 | 2025 | SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation · ICCV 2025 |
Machine learning › Optimization for machine learning
multi-task optimization |
0.9 | 1 | 2025 | SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation · ICCV 2025 |
Machine learning › Optimization for machine learning › gradient-based optimization
sharpness-aware minimization |
0.9 | 1 | 2025 | SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation · ICCV 2025 |
Methods — techniques the papers use, named apart from their topics
sharpness-aware minimization · 0.9gradient perturbation · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation
Hao Ban, Gokul Ram Subramani, Kaiyi Ji |
ICCV | 2 |