A Scalable Algorithm for Structured Kernel Feature Selection

Kernel methods are powerful tools for nonlinear feature representation. Incorporated with structured LASSO, the kernelized structured LASSO is an effective feature selection approach that can preserve the nonlinear input-output relationships as well as the structured sparseness. But as the data dimension increases, the method can quickly become computationally prohibitive. In this paper we propose a stochastic optimization algorithm that can...