Search Results for author:
Found 2 papers, 1 papers with code
The Optimality of Kernel Classifiers in Sobolev Space
Kernel methods are widely used in machine learning, especially for classification problems.
Relaxing the Assumptions of Knockoffs by Conditioning
The recent paper Cand\`es et al. (2018) introduced model-X knockoffs, a method for variable selection that provably and non-asymptotically controls the false discovery rate with no restrictions or assumptions on the dimensionality of the data or the conditional distribution of the response given the covariates.
Methodology
Cannot find the paper you are looking for? You can
Submit a new open access paper.
