Name
Abstract | ||
|---|---|---|
This work presents a new approach which derives a learned data representation method through matrix factorization on the complex domain. In particular, we introduce an encoding matrix-a new representation of data-that satisfies the simplicial constraint of the projective basis matrix on the field of complex numbers. A complex optimization framework is provided. It employs the gradient descent method and computes the derivative of the cost function based on Wirtinger's calculus. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1587/transinf.2017EDL8115 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
complex matrix factorization, data representation, image clustering, gradient descent method | External Data Representation,Pattern recognition,Computer science,Matrix decomposition,Artificial intelligence | Journal |
Volume | Issue | ISSN |
E100D | 12 | 1745-1361 |
Citations | PageRank | References |
1 | 0.36 | 8 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Viet-Hang Duong | 1 | 2 | 2.75 |
| Manh-Quan Bui | 2 | 1 | 1.37 |
| Jian-Jiun Ding | 3 | 738 | 88.09 |
| Yuan-Shan Lee | 4 | 23 | 8.51 |
| Bach-Tung Pham | 5 | 1 | 1.37 |
| Pham The Bao | 6 | 22 | 7.70 |
| Jia-Ching Wang | 7 | 515 | 58.13 |