Preprints

On the testing of multiple hypothesis in sliced inverse regression
Zhigen Zhao, Xin Xing
Arxiv

Robust Flow-based Conformal Inference (FCI) with Statistical Guarantee
Youhui Ye, Meimei Liu, Xin Xing
Arxiv

Publications

Minimax Nonparametric Multi-sample Test
Xin Xing, Zuofeng Shang, Pang Du, Ping Ma, Wenxuan Zhong, Jun S. Liu
Statistica Sinica, 2023 (to appear)

A Scale-free Approach for False Discovery Rate Control in Generalized Linear Models (with discussion)
Chenguang Dai, Buyu Lin, Xin Xing, Jun S. Liu
Journal of the American Statistical Association (JASA), 2023 (to appear)

False Discovery Rate Control via Data Splitting
Chenguang Dai, Buyu Lin, Xin Xing, Jun S. Liu
Journal of the American Statistical Association (JASA), 2022

Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms
Ping Ma, Yongkai Chen, Xinlian Zhang, Xin Xing, Jingyi Ma, and Michael Mahoney
Journal of Machine Learning Research (JMLR), 2022

Model-based Sparse Coding beyond Gaussian Independent Model
Xin Xing, Rui Xie, Wenxuan Zhong
Computational Statistics and Data Analysis (CSDA), 2022

Controlling False Discovery Rate Using Gaussian Mirrors
Xin Xing, Zhigen Zhao, Jun S. Liu
Journal of the American Statistical Association (JASA), 2021

Minimax Nonparametric Parallelism Test [Software]
Xin Xing, Meimei Liu, Ping Ma, Wenxuan Zhong
Journal of Machine Learning Research (JMLR), 2020

Reduction of mNAT1/hNAT2 Contributes to Cerebral Endothelial Necroptosis and Aβ Accumulation in Alzheimer’s Disease
Chengyu Zou, Lauren Mifflin, Zhirui Hu, Tian Zhang, Bing Shan, Huibing Wang, Xin Xing, Hong Zhu, Xian Adiconis, Joshua Z Levin, Fupeng Li, Chuan-Fa Liu, Jun S Liu, Junying Yuan
Cell Reports, 2020

Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks
Xin Xing, Yu Gui, Chenguang Dai, Jun S. Liu
IEEE ICMLA, 2020

Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks
Xin Xing, Long Sha, Pengyu Hong, Zuofeng Shang, Jun S. Liu
International Conference on Learning Representations (ICLR), 2020

Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms
Ping Ma, Xinlian Zhang, Xin Xing, Jinyi Ma, Michael Mahoney
International Conference on ArtificialIntelligence and Statistics (AISTATS), 2020

MetaBMF: A Scalable Binning Algorithm for Large-scale Reference-free Metagenomic Studies [Software]
Terry Ma, Di Xiao, Xin Xing (Corresponding Author)
Bioinformatics, 2019

MetaGen: Reference-free Learning with Multiple Metagenomic Samples [Software]
Xin Xing, Jun S. Liu, Wenxuan Zhong
Genome Biology, 2018

A Scalable Reference-Free Metagenomic Binning Pipeline
Terry Ma, Xin Xing
International Symposium on Bioinformatics Research and Applications, 2018

Sufficient Dimension Reduction for Tensor Data
Yiwen Liu, Xin Xing, Wenxuan Zhong
Handbook of Big Data Analytics, Springer, 2018

Tensor Sufficient Dimension Reduction
Wenxuan Zhong, Xin Xing, Kenneth Suslick
WIREs Computational Statistics, 2015

Robust Minimum Variance Portfolio with L-infinity Constraints
Xin Xing, Jinjin Hu, Yaning Yang
Journal of Banking & Finance, 2014

Joint Semiparametric Mean-Covariance modeling by Moving Average Cholesky Decomposition for Longitudinal Data
Xin Xing, Meimei Liu, Weiping Zhang
Journal of University of Science and Technology of China, 2013

Grants

(PI)NSF ATD 2022-2024

NVIDIA GPU Grant for Accelerated Data Science 2019

Research Highlights

Research is highlighted on the website of graduate school of UGA.

Research is highlighted on the website of Pittsburgh Supercomputer Center.