Supervised context-aware non-negative matrix factorization to handle high-dimensional high-correlated imbalanced biomedical data
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/7958416/7965814/07966428.pdf?arnumber=7966428
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis;Scientific Reports;2024-05-17
2. Community Detection in Signed Networks Based on Normalized Laplacian Matrix and Convex Non-negative Matrix Factorization;2023 2nd International Conference on Automation, Robotics and Computer Engineering (ICARCE);2023-12-14
3. Identification of Cancer Risk Groups through Multi-Omics Integration using Autoencoder and Tensor Analysis;2023-09-13
4. Non-negative Matrix Factorization: A Survey;The Computer Journal;2021-07
5. Feature Selection for High-Dimensional and Imbalanced Biomedical Data Based on Robust Correlation Based Redundancy and Binary Grasshopper Optimization Algorithm;Genes;2020-06-27
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