767 citations · 4.4k across the 70 of their papers we have counts for
8 papers · 1 filter
Scaling SVM and Least Absolute Deviations via Exact Data Reduction
Jie Wang, Peter Wonka, Jieping Ye
The support vector machine (SVM) is a widely used method for classification. Although many efforts have been devoted to develop efficient solvers, it remains challenging to apply S…
A quantum network of clocks
Peter Kómár, Eric M. Kessler, Michael Bishof +4
The development of precise atomic clocks has led to many scientific and technological advances that play an increasingly important role in modern society. Shared timing information…
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…
Dictionary LASSO: Guaranteed Sparse Recovery under Linear Transformation
Ji Liu, Lei Yuan, Jieping Ye
We consider the following signal recovery problem: given a measurement matrix and a noisy observation vector constructed from $c…