Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
The problem of automatic feature selection/weighting in kernel methods is examined. We work on a formulation that optimizes both the weights of features and the parameters of the ...
This paper presents an application of multiple kernels like Kernel Basis to the Relevance Vector Machine algorithm. The framework of kernel machines has been a source of many works...