Name
Abstract | ||
|---|---|---|
Predictive modeling of large-scale spatio-temporal data is an important but challenging problem as it requires training models that can simultaneously predict the target variables of interest at multiple locations while preserving the spatial and temporal dependencies of the data. In this paper, we investigate the effectiveness of applying a multi-task learning approach based on supervised tensor ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TKDE.2019.2956713 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | DocType | Volume |
Tensile stress,Data models,Predictive models,Task analysis,Meteorology,Data mining,Indexes | Journal | 33 |
Issue | ISSN | Citations |
6 | 1041-4347 | 1 |
PageRank | References | Authors |
0.35 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xu Jianpeng | 1 | 45 | 5.87 |
| Jiayu Zhou | 2 | 765 | 56.69 |
| Pang-ning Tan | 3 | 2542 | 162.00 |
| Xi Liu | 4 | 122 | 20.80 |
| Lifeng Luo | 5 | 23 | 6.40 |