Jul 4, 2017 · Abstract:We propose a method for feature selection that employs kernel-based measures of independence to find a subset of covariates that is ...
We propose a method for feature selection that employs kernel-based measures of independence to find a subset of covariates that is maximally predictive of ...
Dec 4, 2017 · We propose a method for feature selection that employs kernel-based measures of independence to find a subset of covariates that is ...
Jan 23, 2018 · The idea is to select the features that maximally account for the dependence of the response on the covariates. We accomplish this by relaxing ...
[PDF] Kernel Feature Selection via Conditional Covariance Minimization
www.jianbochen.me › poster_ccm
We propose a method for feature selection that employs kernel-based measures of independence to find a subset of covariates that is maximally predictive of the ...
A method for feature selection that employs kernel-based measures of independence to find a subset of covariates that is maximally predictive of the ...
Oct 20, 2018 · We propose a method for feature selection that employs kernel-based measures of independence to find a subset of covariates that is ...
@incollection{NIPS2017_7270, title = {Kernel Feature Selection via Conditional Covariance Minimization} ... feature-selection-via-conditional-covariance- ...
Kernel Feature Selection via Conditional Covariance Minimization. Reviewer 1. In this paper, authors propose a new nonlinear feature selection based on kernels.
Jul 4, 2017 · PDF | We propose a framework for feature selection that employs kernel-based measures of independence to find a subset of covariates that is ...