Kazuki Koyama

Effective Nonlinear Feature Selection Method based on HSIC Lasso and with Variational Inference

HSIC Lasso is one of the most effective sparse nonlinear feature selection methods based on the Hilbert-Schmidt independence criterion. We propose an adaptive nonlinear feature selection method, which is based on the HSIC Lasso, that uses a stochastic model with a family of super-Gaussian prior dist…