Name
Abstract | ||
|---|---|---|
•Firstly, we consider a new yet practical DA scenario, called sparsely-labeled source assisted domain adaptation.•Secondly, we propose a unified framework to jointly seek cluster centroids, source and target labels, and domain-invariant features.•Thirdly, we construct an optimization strategy to solve the objective function efficiently. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.patcog.2020.107803 | Pattern Recognition |
Keywords | DocType | Volume |
Domain adaptation,Sparsely-labeled source,Semi-supervised clustering,Label propagation | Journal | 112 |
Issue | ISSN | Citations |
1 | 0031-3203 | 1 |
PageRank | References | Authors |
0.35 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Wang | 1 | 1 | 0.35 |
| Shenglun Chen | 2 | 4 | 1.72 |
| Yuankai Xiang | 3 | 1 | 0.35 |
| Jing Sun | 4 | 1 | 0.68 |
| Haojie Li | 5 | 32 | 9.03 |
| Zhihui Wang | 6 | 19 | 7.84 |
| Fuming Sun | 7 | 2 | 3.40 |
| Zhengming Ding | 8 | 536 | 39.14 |
| Baopu Li | 9 | 5 | 3.79 |