# Efficient Multi-View Clustering via Unified and Discrete Bipartite Graph Learning

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/efficient-multi-view-clustering-via-unified-and-discrete-bipartite-graph/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Si-Guo Fang,Dong Huang,Xiao-Sha Cai,Chang‐Dong Wang,Chaobo He,Yong Tang |
| Citations | 183 |
| DOI | 10.1109/tnnls.2023.3261460 |
| Fields | Computer Science,Physics and Astronomy |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4360753265 |
| PMID | 37030820 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Dong Huang](https://scholariq.org/researchers/dong-huang/)

## Paper journal

- [IEEE Transactions on Neural Networks and Learning Systems](https://scholariq.org/journals/ieee-transactions-on-neural-networks-and-learning-systems/)

## Paper primary topic

- [Complex Network Analysis Techniques](https://scholariq.org/topics/complex-network-analysis-techniques/)

## Paper topics

- [Complex Network Analysis Techniques](https://scholariq.org/topics/complex-network-analysis-techniques/)
- [Advanced Clustering Algorithms Research](https://scholariq.org/topics/advanced-clustering-algorithms-research/)
- [Advanced Graph Neural Networks](https://scholariq.org/topics/advanced-graph-neural-networks/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.