Safe and Efficient Screening For Sparse Support Vector Machine
classification
💻 cs.LG
stat.ML
keywords
efficientscreeningsparsetechniquemachineprocesssafesupport
read the original abstract
Screening is an effective technique for speeding up the training process of a sparse learning model by removing the features that are guaranteed to be inactive the process. In this paper, we present a efficient screening technique for sparse support vector machine based on variational inequality. The technique is both efficient and safe.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.