Name
Title | ||
|---|---|---|
Semantic Feature Learning for Heterogeneous Multitask Classification via Non-Negative Matrix Factorization. |
Abstract | ||
|---|---|---|
Multitask learning (MTL) aims to learn multiple related tasks simultaneously instead of separately to improve the generalization performance of each task. Most existing MTL methods assumed that the multiple tasks to be learned have the same feature representation. However, this assumption may not hold for many real-world applications. In this paper, we study the problem of MTL with heterogeneous f... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCYB.2017.2732818 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Semantics,Bipartite graph,Correlation,Predictive models,Feature extraction,Cybernetics,Computers | Multi-task learning,Matrix decomposition,Bipartite graph,Feature extraction,Non-negative matrix factorization,Artificial intelligence,Covariance matrix,Semantic feature,Semantics,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
48 | 8 | 2168-2267 |
Citations | PageRank | References |
0 | 0.34 | 14 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fuzhen Zhuang | 1 | 827 | 75.28 |
| Xuebing Li | 2 | 0 | 0.68 |
| Xin Jin | 3 | 117 | 6.04 |
| Dapeng Zhang | 4 | 3 | 3.41 |
| Lirong Qiu | 5 | 60 | 12.70 |
| Qing He | 6 | 34 | 7.02 |