A Novel Real Time Method of Signal Strength Based Indoor Localization. - Letian Ye; Zhi Geng; Lingzhou Xue; Zhihai Liu (ICCSA (1), 2007)

A gradually locating method of indoor locating estimation based on likelihood. - Letian Ye; Zhihai Liu; Lingzhou Xue; Ping He; Zhi Geng (Mobility Conference, 2007)

Minimax optimal estimation of general bandable covariance matrices. - Lingzhou Xue; Hui Zou (J. Multivar. Anal., 2013)

Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection. - Shiqian Ma; Lingzhou Xue; Hui Zou (Neural Comput., 2013)

Discovery of Causal Time Intervals. - Zhenhui Li; Guanjie Zheng; Amal Agarwal; Lingzhou Xue; Thomas Lauvaux (SDM, 2017)

Model-Based Clustering of Nonparametric Weighted Networks. - Amal Agarwal; Lingzhou Xue (CoRR, 2017)

A Selective Overview of Sparse Principal Component Analysis. - Hui Zou; Lingzhou Xue (Proc. IEEE, 2018)

Condition-adaptive fused graphical lasso (CFGL): An adaptive procedure for inferring condition-specific gene co-expression network. - Yafei Lyu; Lingzhou Xue; Feipeng Zhang; Hillary Koch; Laura M. Saba; Katerina J. Kechris; Qunhua Li (PLoS Comput. Biol., 2018)

Nonparametric Finite Mixture of Gaussian Graphical Models. - Kevin H. Lee; Lingzhou Xue (Technometrics, 2018)

An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA. - Shixiang Chen; Shiqian Ma; Lingzhou Xue; Hui Zou (CoRR, 2019)

Hawkesian Graphical Event Models. - Xiufan Yu; Karthikeyan Shanmugam; Debarun Bhattacharjya; Tian Gao; Dharmashankar Subramanian; Lingzhou Xue (PGM, 2020)

Model-based clustering of time-evolving networks through temporal exponential-family random graph models. - Kevin H. Lee; Lingzhou Xue; David R. Hunter (J. Multivar. Anal., 2020)

Model-Based Clustering of Nonparametric Weighted Networks With Application to Water Pollution Analysis. - Amal Agarwal; Lingzhou Xue (Technometrics, 2020)

An Alternating Manifold Proximal Gradient Method for Sparse Principal Component Analysis and Sparse Canonical Correlation Analysis. - Shixiang Chen; Shiqian Ma; Lingzhou Xue; Hui Zou (INFORMS J. Optim., 2020)

An additive graphical model for discrete data. - Jun Tao; Bing Li; Lingzhou Xue (CoRR, 2021)

Improving neural network robustness through neighborhood preserving layers. - Bingyuan Liu; Christopher Malon; Lingzhou Xue; Erik Kruus (Image Vis. Comput., 2022)

Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold. - Bokun Wang; Shiqian Ma; Lingzhou Xue (J. Mach. Learn. Res., 2022)

A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis. - Zhongruo Wang; Bingyuan Liu; Shixiang Chen; Shiqian Ma; Lingzhou Xue; Hongyu Zhao 003 (INFORMS J. Optim., 2022)

A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution. - Jun Tao; Qian Chen; James W. Snyder Jr.; Arava Sai Kumar; Amirhossein Meisami; Lingzhou Xue (CoRR, 2023)

Identification of microbial features in multivariate regression under false discovery rate control. - Arun Srinivasan; Lingzhou Xue; Xiang Zhan (Comput. Stat. Data Anal., 2023)

Federated Q-Learning: Linear Regret Speedup with Low Communication Cost. - Zhong Zheng; Fengyu Gao; Lingzhou Xue; Jing Yang 002 (ICLR, 2024)

A Copula Graphical Model for Multi-Attribute Data using Optimal Transport. - Qi Zhang; Bing Li; Lingzhou Xue (CoRR, 2024)

Smoothed Robust Phase Retrieval. - Zhong Zheng; Lingzhou Xue (CoRR, 2024)

The Effect of Personalization in FedProx: A Fine-grained Analysis on Statistical Accuracy and Communication Efficiency. - Xin Yu; Zelin He; Ying Sun; Lingzhou Xue; Runze Li (CoRR, 2024)

Nonlinear sufficient dimension reduction for distribution-on-distribution regression. - Qi Zhang; Bing Li; Lingzhou Xue (J. Multivar. Anal., 2024)

A New Inexact Proximal Linear Algorithm With Adaptive Stopping Criteria for Robust Phase Retrieval. - Zhong Zheng; Shiqian Ma; Lingzhou Xue (IEEE Trans. Signal Process., 2024)

Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition. - Zhong Zheng; Haochen Zhang; Lingzhou Xue (ICLR, 2025)

Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost. - Zhong Zheng; Haochen Zhang; Lingzhou Xue (ICLR, 2025)

Gap-Dependent Bounds for Federated Q-learning. - Haochen Zhang; Zhong Zheng; Lingzhou Xue (CoRR, 2025)

AltLoRA: Towards Better Gradient Approximation in Low-Rank Adaptation with Alternating Projections. - Xin Yu; Yujia Wang; Jinghui Chen; Lingzhou Xue (CoRR, 2025)

Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning. - Haochen Zhang; Zhong Zheng; Lingzhou Xue (CoRR, 2025)

Theoretical Guarantees for Sparse Principal Component Analysis Based on the Elastic Net. - Haoyi Yang; Teng Zhang 002; Lingzhou Xue (IEEE Trans. Inf. Theory, 2025)