This repository implements tensor completion methods using Overlapped Tensor Nuclear Norm (OTNN) and Latent Tensor Nuclear Norm (LTNN) algorithms [1]. These methods are designed to recover missing entries in multi-dimensional data (tensors).
[1] Qiu, Y., Zhou, G., Wang, A., Zhao, Q., & Xie, S. (2024). Balanced Unfolding Induced Tensor Nuclear Norms for High-Order Tensor Completion. IEEE Transactions on Neural Networks and Learning Systems, early access.
- Tensor Toolbox in main dir (for some auxiliary functions),
If you find this repository useful for your research, please cite the following paper:
@article{qiu2024balanced,
title={Balanced Unfolding Induced Tensor Nuclear Norms for High-Order Tensor Completion},
author={Qiu, Yuning and Zhou, Guoxu and Wang, Andong and Zhao, Qibin and Xie, Shengli},
journal={IEEE Transactions on Neural Networks and Learning Systems},
year={2024},
publisher={IEEE}
}