MTD

Code for paper: Masked Two-channel Decoupling Framework for Incomplete Multi-view Weak Multi-label Learning

You can run 'python main.py' for a demo! The original link to the five datasets is not available now, you can download the datesets and pre-processed incomplete datesets from here.

Typo correction:

1. In the denominator of Eq.(1), "u=v" should be "u!=v".

2. It should be {D_{v}: (S^{(v)}+O^{(v)}) \rightarrow \bar{X}^{(v)}}, instead of {{D}{v}: S^{(v)} \rightarrow \bar{X}^{(v)}}. The input of decoder D{v} is the sum of shared and private features.

If this code is helpful to you, please cite the following paper:

@inproceedings{liu2024masked,
  title={Masked Two-channel Decoupling Framework for Incomplete Multi-view Weak Multi-label Learning},
  author={Liu, Chengliang and Wen, Jie and Liu, Yabo and Huang, Chao and Wu, Zhihao and Luo, Xiaoling and Xu, Yong},
  booktitle={Advances in Neural Information Processing Systems},
  volume={36},
  year={2024}
}

Please get in touch with me if you have any questions about running this code! [email protected]