A Robust Regularization Path Algorithm for $\nu $ -Support Vector Classification

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

470 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Mechanics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/7562f6fc4d4fb488afc4a1e47e2f7cdf6b9e3639

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. Ke Yan
2. Yu Xue

In Computer Vision and Pattern Recognition

1. Ke Yan
2. Wu Deng
3. Xinhua Yang
4. Yu Xue
5. Huimin Zhao

Citations in the corpus

• Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks (2016, unknown): “org) extra transmission energy cost [7].”
• A novel intelligent diagnosis method using optimal LS-SVM with improved PSO algorithm (2017, background): “Gu and Sheng (2017) proposed a regularization path algorithm for ν -support vector classi-fication.”
• A hybrid feature selection algorithm for gene expression data classification (2017, methodology): “To demonstrate the effectiveness of the MIMAGA-Selection algorithm, we apply three existing feature selection algorithms: ReliefF [39,40] , sequential forward selection (SFS) [41,42] and MIM on the same datasets with the same target gene numbers.”