Efficient algorithm for tensor noise reduction and completion of ordinal tensor data based on the cumulative link model. The algorithm employs the alternating optimization approach. The detailed algorithm description can be found in Lee and Wang, Proceedings of International Conference on Machine Learning, 119:5778-5788, 2020.
| Version: | 0.2.0 |
| Imports: | pracma, MASS, rTensor, methods |
| Published: | 2020-12-13 |
| Author: | Chanwoo Lee, Miaoyan Wang |
| Maintainer: | Chanwoo Lee <chanwoo.lee at wisc.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://proceedings.mlr.press/v119/lee20i.html |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | tensorordinal results |
| Reference manual: | tensorordinal.pdf |
| Package source: | tensorordinal_0.2.0.tar.gz |
| Windows binaries: | r-devel: tensorordinal_0.2.0.zip, r-release: tensorordinal_0.2.0.zip, r-oldrel: tensorordinal_0.2.0.zip |
| macOS binaries: | r-release: tensorordinal_0.2.0.tgz, r-oldrel: tensorordinal_0.2.0.tgz |
| Old sources: | tensorordinal archive |
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