The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Efficient algorithms for tensor noise reduction and completion. This package includes a suite of parametric and nonparametric tools for estimating tensor signals from noisy, possibly incomplete observations. The methods allow a broad range of data types, including continuous, binary, and ordinal-valued tensor entries. The algorithms employ the alternating optimization. The detailed algorithm description can be found in the following three references.
| Version: | 0.2.0 |
| Imports: | pracma, methods, utils, tensorregress, MASS |
| Published: | 2023-04-14 |
| DOI: | 10.32614/CRAN.package.TensorComplete |
| Author: | Chanwoo Lee, Miaoyan Wang |
| Maintainer: | Chanwoo Lee <chanwoo.lee at wisc.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | Chanwoo Lee and Miaoyan Wang. Tensor denoising and completion based on ordinal observations. ICML, 2020. http://proceedings.mlr.press/v119/lee20i.html Chanwoo Lee and Miaoyan Wang. Beyond the Signs: Nonparametric tensor completion via sign series. NeurIPS, 2021. https://papers.nips.cc/paper/2021/hash/b60c5ab647a27045b462934977ccad9a-Abstract.html Chanwoo Lee, Lexin Li, Hao Helen Zhang, and Miaoyan Wang. Nonparametric trace regression in high dimensions via sign series representation. 2021. https://arxiv.org/abs/2105.01783 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | TensorComplete results |
| Reference manual: | TensorComplete.pdf |
| Package source: | TensorComplete_0.2.0.tar.gz |
| Windows binaries: | r-devel: TensorComplete_0.2.0.zip, r-release: TensorComplete_0.2.0.zip, r-oldrel: TensorComplete_0.2.0.zip |
| macOS binaries: | r-release (arm64): TensorComplete_0.2.0.tgz, r-oldrel (arm64): TensorComplete_0.2.0.tgz, r-release (x86_64): TensorComplete_0.2.0.tgz, r-oldrel (x86_64): TensorComplete_0.2.0.tgz |
| Old sources: | TensorComplete archive |
Please use the canonical form https://CRAN.R-project.org/package=TensorComplete to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.