Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel
Support vector machines (SVMs) with the gaussian (RBF) kernel have been popular for practical use. Model selection in this class of SVMs involves two hyper parameters: the penal...
Publications
5 shownA dual coordinate descent method for large-scale linear SVM
In many applications, data appear with a huge number of instances as well as features. Linear Support Vector Machines (SVM) is one of the most popular tools to deal with such la...
Trust Region Newton Method for Logistic Regression
Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method...
Trust region Newton methods for large-scale logistic regression
Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method...
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as...
Frequent Co-Authors
Researcher Info
- h-index
- 5
- Publications
- 5
- Citations
- 3,220
- Institution
- National University of Singapore
External Links
Impact Metrics
h-index
5
h-index: Number of publications with at least h citations each.