A Unified Feature Selection Framework for Graph Embedding on High Dimensional Data

By Marcus Chen, Ivor Wai-Hung Tsang, Mingkui Tan, Tat-Jen Cham. 2015

35 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Kevin Chen-Chuan Chang
2. Vincent Wenchen Zheng
3. Shirui Pan
4. Hongyun Cai
5. Feng Xia
6. Ke Sun
7. Liangtian Wan
8. Abdul Aziz

In Computer Vision and Pattern Recognition

1. Vincent Wenchen Zheng
2. Kevin Chen-Chuan Chang
3. Hongyun Cai
4. Ke Sun
5. Feng Xia
6. Shirui Pan
7. Huan Liu
8. Jiliang Tang

In Molecular Biology

1. Hongyun Cai
2. Ke Sun
3. Kevin Chen-Chuan Chang
4. Liangtian Wan
5. Abdul Aziz
6. Feng Xia
7. Shirui Pan
8. Vincent Wenchen Zheng

Citations in the corpus

• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications (2017, background): “cation ([81], [82]), image clustering [101], image segmentation [154], pattern recognition [80], and so on.”
• Graph Learning: A Survey (2021, methodology): “The general framework has been designed in [68], and the graph Laplacian matrix factorization based graph learning methods have been summarized”