626 citations · 910 across the 11 of their papers we have counts for
11 papers
Neyman-Pearson Classification under High-Dimensional Settings
Anqi Zhao, Yang Feng, Lie Wang +1
Most existing binary classification methods target on the optimization of the overall classification risk and may fail to serve some real-world applications such as cancer diagnosi…
Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification
Robert Vanderbei, Han Liu, Lie Wang +1
In this paper we present two new approaches to efficiently solve large-scale compressed sensing problems. These two ideas are independent of each other and can therefore be used ei…
Estimating the Ratio of Two Functions in a Nonparametric Regression Model
Jelena Markovic, Lie Wang
Due to measurement noise, a common problem in in various fields is how to estimate the ratio of two functions. We consider this problem of estimating the ratio of two functions in…
Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery
Han Liu, Lie Wang, Tuo Zhao
We propose a calibrated multivariate regression method named CMR for fitting high dimensional multivariate regression models. Compared with existing methods, CMR calibrates regular…
TIGER: A Tuning-Insensitive Approach for Optimally Estimating Gaussian Graphical Models
Han Liu, Lie Wang
We propose a new procedure for estimating high dimensional Gaussian graphical models. Our approach is asymptotically tuning-free and non-asymptotically tuning-insensitive: it requi…
L1 penalized LAD estimator for high dimensional linear
Lie Wang
In this paper, the high-dimensional sparse linear regression model is considered, where the overall number of variables is larger than the number of observations. We investigate th…