6 citations · 12 across the 9 of their papers we have counts for
9 papers
Robust and Sparse Generalized Linear Models for High-Dimensional Data via Maximum Mean Discrepancy
Xiaoning Kang, Lulu Kang
High-dimensional datasets are frequently subject to contamination by outliers and heavy-tailed noise, which can severely bias standard regularized estimators like the Lasso. While…
Weighted Average Ensemble for Cholesky-based Covariance Matrix Estimation
Xiaoning Kang, Zhenguo Gao, Xi Liang +1
The modified Cholesky decomposition (MCD) is an efficient technique for estimating a covariance matrix. However, it is known that the MCD technique often requires a pre-specified v…
On Block Cholesky Decomposition for Sparse Inverse Covariance Estimation
Xiaoning Kang, Jiayi Lian, Xinwei Deng
The modified Cholesky decomposition is popular for inverse covariance estimation, but often needs pre-specification on the full information of variable ordering. In this work, we p…
Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing
Xiaoyu Chen, Xiaoning Kang, Ran Jin +1
Fog manufacturing can greatly enhance traditional manufacturing systems through distributed Fog computation units, which are governed by predictive computational workload offloadin…
A Generative Approach to Joint Modeling of Quantitative and Qualitative Responses
Xiaoning Kang, Lulu Kang, Wei Chen +1
In many scientific areas, data with quantitative and qualitative (QQ) responses are commonly encountered with a large number of predictors. By exploring the association between QQ…
Bayesian Auxiliary Variable Model for Birth Records Data with Qualitative and Quantitative Responses
Xiaoning Kang, Shyam Ranganathan, Lulu Kang +2
Many applications involve data with qualitative and quantitative responses. When there is an association between the two responses, a joint model will provide improved results than…
Multivariate Regression of Mixed Responses for Evaluation of Visualization Designs
Xiaoning Kang, Xiaoyu Chen, Ran Jin +2
Information visualization significantly enhances human perception by graphically representing complex data sets. The variety of visualization designs makes it challenging to effici…
On Variable Ordination of Modified Cholesky Decomposition for Sparse Covariance Matrix Estimation
Xiaoning Kang, Xinwei Deng
Estimation of large sparse covariance matrices is of great importance for statistical analysis, especially in the high-dimensional settings. The traditional approach such as the sa…
An Improved Modified Cholesky Decomposition Method for Precision Matrix Estimation
Xiaoning Kang, Xinwei Deng
The modified Cholesky decomposition is commonly used for precision matrix estimation given a specified order of random variables. However, the order of variables is often not avail…