EDBT 2026 Demo / reviewers in the wild / expert
Ho-Pang Hsu
dblp:175/3384
· 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
Systems, architecture and hardware · 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 · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Recommender systems · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Efficient and distributed learning › distributed training › distributed training systems
large-scale distributed training |
0.9 | 1 | 2025 | Primus: Unified Training System for Large-Scale Deep Learning Recommendation Models · USENIX ATC 2025 |
Recommender systems
neural recommendation |
0.3 | 1 | 2025 | Primus: Unified Training System for Large-Scale Deep Learning Recommendation Models · USENIX ATC 2025 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Primus: Unified Training System for Large-Scale Deep Learning Recommendation Models
Jixi Shan, Xiuqi Huang, Hongyue Mao, Ho-Pang Hsu, Hang Cheng, Xiaofeng Gao 0001, Shiru Ren, Jiaxiao Zheng, Lele Yu, Guihai Chen |
USENIX ATC | 5 |