553 citations · 754 across the 10 of their papers we have counts for
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Safe and Efficient Screening For Sparse Support Vector Machine
Zheng Zhao, Jun Liu
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…
A Safe Screening Rule for Sparse Logistic Regression
Jie Wang, Jiayu Zhou, Jun Liu +2
The l1-regularized logistic regression (or sparse logistic regression) is a widely used method for simultaneous classification and feature selection. Although many recent efforts h…
Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods
Jie Wang, Jun Liu, Jieping Ye
Sparse learning has recently received increasing attention in many areas including machine learning, statistics, and applied mathematics. The mixed-norm regularization based on the…
Safe Screening With Variational Inequalities and Its Application to LASSO
Jun Liu, Zheng Zhao, Jie Wang +1
Sparse learning techniques have been routinely used for feature selection as the resulting model usually has a small number of non-zero entries. Safe screening, which eliminates th…