Package: TensorComplete
Type: Package
Title: Tensor Noise Reduction and Completion Methods
Version: 0.2.0
Author: Chanwoo Lee <chanwoo.lee@wisc.edu>, Miaoyan Wang <miaoyan.wang@wisc.edu>
Maintainer: Chanwoo Lee <chanwoo.lee@wisc.edu>
Imports: pracma, methods, utils, tensorregress, MASS
Description: 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.
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
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2023-04-13 03:26:51 UTC; chanwoolee
Repository: CRAN
Date/Publication: 2023-04-14 08:50:11 UTC
Built: R 4.1.3; ; 2023-04-17 14:50:54 UTC; windows
