Name
Abstract | ||
|---|---|---|
•A regularized version of the locally linear embedding algorithm is proposed to handle additive noise.•The algorithm has been shown to perform well in practice.•In addition, an algorithm is proposed to automatically select the regularization parameter. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.patrec.2019.02.030 | Pattern Recognition Letters |
Keywords | Field | DocType |
Cross validation,Dimension reduction,Regularization | Noisy data,Embedding,Dimensionality reduction,Pattern recognition,Linearity,Algorithm,Nonlinear dimension reduction,Artificial intelligence,Distortion,Mathematics | Journal |
Volume | ISSN | Citations |
123 | 0167-8655 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Justin Wang | 1 | 0 | 0.34 |
| Raymond K. W. Wong | 2 | 2 | 1.39 |
| Thomas C. M. Lee | 3 | 88 | 17.54 |