Unsupervised Multi-View Learning

IJCAI 2019 pp. 6442-6443

doi:10.24963/IJCAI.2019/910 /ijcai/2019/huang2019ijcai-unsupervised/

Abstract

Unsupervised multi-view learning is a hot research topic. The main challenge lies in how to integrate information from different views to enhance the unsupervised learning performance. In this paper, we present our research works on multi-view data clustering and multi-view network community detection respectively. The main contributions are summarized by emphasizing the challenges we have addressed. In addition, the ongoing work and the future work are briefly presented.

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Text

Huang. "Unsupervised Multi-View Learning." International Joint Conference on Artificial Intelligence, 2019. doi:10.24963/IJCAI.2019/910

Markdown

[Huang. "Unsupervised Multi-View Learning." International Joint Conference on Artificial Intelligence, 2019.](https://mlanthology.org/ijcai/2019/huang2019ijcai-unsupervised/) doi:10.24963/IJCAI.2019/910

BibTeX

@inproceedings{huang2019ijcai-unsupervised,
  title     = {{Unsupervised Multi-View Learning}},
  author    = {Huang, Ling},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2019},
  pages     = {6442-6443},
  doi       = {10.24963/IJCAI.2019/910},
  url       = {https://mlanthology.org/ijcai/2019/huang2019ijcai-unsupervised/}
}