Structural Minimax Probability Machine

By Bin Gu, Xingming Sun, Victor S. Sheng. IEEE Transactions on Neural Networks and Learning Systems, 2017

348 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/fe2b6e2abc22bdd4338953ec47eea276c75c9819

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. Shifei Ding
2. Lingheng Meng
3. Yu Xue

In Computer Vision and Pattern Recognition

1. Shifei Ding
2. Wu Deng
3. Lingheng Meng
4. Xinhua Yang
5. Yu Xue
6. Huimin Zhao

In Molecular Biology

1. Shifei Ding
2. Lingheng Meng
3. Yu Xue

Citations in the corpus

• A novel intelligent diagnosis method using optimal LS-SVM with improved PSO algorithm (2017, background): “Gu et al. (2017) proposed a structural minimax probability machine for constructing a margin clas-sifier.”
• Research on denoising sparse autoencoder (2016, methodology): “Apart from that autoencoder can also be used in image segmentation [17], cluster [18] and classification [19, 20].”