Name
Abstract | ||
|---|---|---|
In this paper, we present a new joint factorization algorithm, called nonnegative tensor cofactorization (NTCoF). The key idea is to simultaneously factorize multiple visual features of the same data into nonnegative dimensionality-reduced representations, and meanwhile, to maximize the correlations of the low-dimensional representations. The data are generally encoded as tensors of arbitrary orde... |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TIP.2014.2327806 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Tensile stress,Linear programming,Correlation,Optimization,Vectors,Convergence,Matrix decomposition | Convergence (routing),Tensor,Pattern recognition,Matrix decomposition,Stress (mechanics),Artificial intelligence,Linear programming,Mathematics | Journal |
Volume | Issue | ISSN |
23 | 9 | 1057-7149 |
Citations | PageRank | References |
0 | 0.34 | 30 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaobai Liu | 1 | 800 | 40.79 |
| Qian Xu | 2 | 47 | 2.92 |
| Shuicheng Yan | 3 | 767 | 25.71 |
| Gang Wang | 4 | 2869 | 135.49 |
| Hai Jin | 5 | 6544 | 644.63 |
| Seong-Whan Lee | 6 | 3756 | 343.90 |