On sparse estimation for semiparametric linear transformation models. - Hao Helen Zhang; Wenbin Lu; Hansheng Wang 002 (J. Multivar. Anal., 2010)

Variance estimation in censored quantile regression via induced smoothing. - Lei Pang; Wenbin Lu; Huixia Judy Wang (Comput. Stat. Data Anal., 2012)

Partially linear single index Cox regression model in nested case-control studies. - Shulian Shang; Mengling Liu; Anne Zeleniuch-Jacquotte; Tess V. Clendenen; Vittorio Krogh; Goran Hallmans; Wenbin Lu (Comput. Stat. Data Anal., 2013)

NPHMC: An R-package for estimating sample size of proportional hazards mixture cure model. - Chao Cai; Songfeng Wang; Wenbin Lu; Jiajia Zhang (Comput. Methods Programs Biomed., 2014)

Sample size calculation for the proportional hazards model with a time-dependent covariate. - Songfeng Wang; Jiajia Zhang; Wenbin Lu (Comput. Stat. Data Anal., 2014)

Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level. - X. Jessie Jeng; Z. John Daye; Wenbin Lu; Jung-Ying Tzeng (PLoS Comput. Biol., 2016)

Sparse Concordance-assisted Learning for Optimal Treatment Decision. - Shuhan Liang; Wenbin Lu; Rui Song 006; Lan Wang (J. Mach. Learn. Res., 2017)

Enabling Low-Overhead Communication in Multi-threaded OpenSHMEM Applications using Contexts. - Wenbin Lu; Tony Curtis; Barbara M. Chapman (PAW-ATM@SC, 2019)

Frequency offset insensitive demodulation algorithm for satellite-based automatic identification system. - Haosu Zhou; Wenbin Lu; Zhenbin Lv; Hui Gu; Zhenfu Liu (Int. J. Satell. Commun. Netw., 2019)

Privacy-preserving content-based image retrieval for mobile computing. - Yong Wang 028; Fei Liu; Zimao Pang; Abdelrhman Hassan; Wenbin Lu (J. Inf. Secur. Appl., 2019)

Determining the Number of Latent Factors in Statistical Multi-Relational Learning. - Chengchun Shi; Wenbin Lu; Rui Song 006 (J. Mach. Learn. Res., 2019)

Identifying individual risk rare variants using protein structure guided local tests (POINT). - Rachel Marceau West; Wenbin Lu; Daniel M. Rotroff; Mélaine A. Kuenemann; Sheng-Mao Chang; Michael C. Wu; Michael J. Wagner; John B. Buse; Alison A. Motsinger-Reif; Denis Fourches; Jung-Ying Tzeng (PLoS Comput. Biol., 2019)

A New Framework for Online Testing of Heterogeneous Treatment Effect. - Miao Yu; Wenbin Lu; Rui Song 006 (AAAI, 2020)

On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies. - Hengrui Cai; Wenbin Lu; Rui Song 006 (ICML, 2020)

Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. - Chengchun Shi; Runzhe Wan; Rui Song 006; Wenbin Lu; Ling Leng (ICML, 2020)

Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health. - Liangyu Zhu; Wenbin Lu; Rui Song 006 (ICML, 2020)

Toward Supporting Multi-GPU Targets via Taskloop and User-Defined Schedules. - Vivek Kale; Wenbin Lu; Anthony Curtis; Abid Muslim Malik; Barbara M. Chapman; Oscar R. Hernandez (IWOMP, 2020)

Kernel Assisted Learning for Personalized Dose Finding. - Liangyu Zhu; Wenbin Lu; Michael R. Kosorok; Rui Song 006 (KDD, 2020)

Checkpointing OpenSHMEM Programs Using Compiler Analysis. - Md Abdullah Shahneous Bari; Debasmita Basu; Wenbin Lu; Tony Curtis; Barbara M. Chapman (FTXS@SC, 2020)

Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings. - Chengchun Shi; Sheng Zhang 027; Wenbin Lu; Rui Song 006 (CoRR, 2020)

Statistical Inference for Online Decision-Making: In a Contextual Bandit Setting. - Haoyu Chen; Wenbin Lu; Rui Song 006 (CoRR, 2020)

Statistical Inference for Online Decision Making via Stochastic Gradient Descent. - Haoyu Chen; Wenbin Lu; Rui Song 006 (CoRR, 2020)

Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space. - Hengrui Cai; Chengchun Shi; Rui Song 006; Wenbin Lu (CoRR, 2020)

Breaking the Curse of Nonregularity with Subagging - Inference of the Mean Outcome under Optimal Treatment Regimes. - Chengchun Shi; Wenbin Lu; Rui Song 006 (J. Mach. Learn. Res., 2020)

Association test using Copy Number Profile Curves (CONCUR) enhances power in rare copy number variant analysis. - Amanda Brucker; Wenbin Lu; Rachel Marceau West; Qi-You Yu; Chuhsing Kate Hsiao; Tzu-Hung Hsiao; Ching-Heng Lin; Patrik K. E. Magnusson; Patrick F. Sullivan; Jin P. Szatkiewicz; Tzu-Pin Lu; Jung-Ying Tzeng (PLoS Comput. Biol., 2020)

Anisotropic Constitutive Model of Intermittent Columnar Jointed Rock Masses Based on the Cosserat Theory. - Wenbin Lu; Zhende Zhu; Xiangcheng Que; Cong Zhang; Yanxin He (Symmetry, 2020)

Model Test Study on the Anisotropic Characteristics of Columnar Jointed Rock Mass. - Zhende Zhu; Xiangcheng Que; Zihao Niu; Wenbin Lu (Symmetry, 2020)

Online Testing of Subgroup Treatment Effects Based on Value Difference. - Miao Yu; Wenbin Lu; Rui Song 006 (ICDM, 2021)

ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning. - Hengrui Cai; Rui Song 006; Wenbin Lu (ICLR, 2021)

Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. - Hengrui Cai; Chengchun Shi; Rui Song 006; Wenbin Lu (NeurIPS, 2021)

OpenSHMEM Active Message Extension for Task-Based Programming. - Wenbin Lu; Tony Curtis; Barbara M. Chapman (OpenSHMEM, 2021)

UCX Programming Interface for Remote Function Injection and Invocation. - Luis E. Peña; Wenbin Lu; Pavel Shamis; Steve Poole 001 (OpenSHMEM, 2021)

Gene-set integrative analysis of multi-omics data using tensor-based association test. - Sheng-Mao Chang; Meng Yang; Wenbin Lu; Yu-Jyun Huang; Yueyang Huang; Hung Hung; Jeffrey C. Miecznikowski; Tzu-Pin Lu; Jung-Ying Tzeng (Bioinform., 2021)

CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search. - Hengrui Cai; Wenbin Lu; Rachel Marceau West; Devan V. Mehrotra; Lingkang Huang (CoRR, 2021)

Jump Interval-Learning for Individualized Decision Making. - Hengrui Cai; Chengchun Shi; Rui Song 006; Wenbin Lu (CoRR, 2021)

Testing error heterogeneity in censored linear regression. - Caiyun Fan; Wenbin Lu; Yong Zhou (Comput. Stat. Data Anal., 2021)

Bring the BitCODE-Moving Compute and Data in Distributed Heterogeneous Systems. - Wenbin Lu; Luis E. Peña; Pavel Shamis; Valentin Churavy; Barbara M. Chapman; Steve Poole 001 (CLUSTER, 2022)

Towards Efficient Remote OpenMP Offloading. - Wenbin Lu; Baodi Shan; Eric Raut; Jie Meng; Mauricio Araya-Polo; Johannes Doerfert; Abid Muslim Malik; Barbara M. Chapman (IWOMP, 2022)

Extending OpenMP and OpenSHMEM for Efficient Heterogeneous Computing. - Wenbin Lu; Shilei Tian; Tony Curtis; Barbara M. Chapman (PAW-ATM@SC, 2022)

A visual identification method for the apple growth forms in the orchard. - Jidong Lv; Hao Xu; Ying Han; Wenbin Lu; Liming Xu; Hailong Rong; Biao Yang; Ling Zou 002; Zhenghua Ma (Comput. Electron. Agric., 2022)

On Learning and Testing of Counterfactual Fairness through Data Preprocessing. - Haoyu Chen; Wenbin Lu; Rui Song 006; Pulak Ghosh (CoRR, 2022)

Mining the Factor Zoo: Estimation of Latent Factor Models with Sufficient Proxies. - Runzhe Wan; Yingying Li; Wenbin Lu; Rui Song 006 (CoRR, 2022)

TransModel: An R Package for Linear Transformation Model with Censored Data. - Jie Zhou; Jiajia Zhang; Wenbin Lu (J. Stat. Softw., 2022)

A Probit Tensor Factorization Model For Relational Learning. - Ye Liu; Rui Song 006; Wenbin Lu; Yanghua Xiao (J. Comput. Graph. Stat., 2022)

Multiply Robust Off-policy Evaluation and Learning under Truncation by Death. - Jianing Chu; Shu Yang; Wenbin Lu (ICML, 2023)

Research and Design of Nand Flash Array From Host to Flash Translation Layer. - Boyang Ding; Songyan Liu; Tao Lv; Yao Liu; Wenbin Lu (IEEE Access, 2023)

Jump Interval-Learning for Individualized Decision Making with Continuous Treatments. - Hengrui Cai; Chengchun Shi; Rui Song 006; Wenbin Lu (J. Mach. Learn. Res., 2023)

Interpretable machine-learning model for real-time, clustered risk factor analysis of sepsis and septic death in critical care. - Zhengyu Jiang; Lulong Bo; Lei Wang; Yan Xie; Jianping Cao; Ying Yao; Wenbin Lu; Xiaoming Deng 004; Tao Yang; Jinjun Bian (Comput. Methods Programs Biomed., 2023)

Research on Real-time Detection and Tracking Algorithm for Low Slow Small Targets Based on the DeepSort. - Yuding Xi; Sufeng Zhuang; Pengyun Wang; Yun Ling; Zhenbin Lv; Wenbin Lu (CACML, 2024)

Linear Contextual Bandits with Interference. - Yang Xu; Wenbin Lu; Rui Song 006 (CoRR, 2024)

Radio Frequency Signal Identification for Unmanned Aerial Vehicles Using Deep Learning Techniques. - Shuo Yang; Huaming Shen; Xiaobei Zhang; Zhenbin Lv; Anping Wang; Wenbin Lu (CNIOT, 2025)

Efficient Causal Decision Making with One-sided Feedback. - Jianing Chu; Shu Yang; Wenbin Lu; Pulak Ghosh (ICLR, 2025)

Medical Knowledge-Based Differential Image Visual Question Answering. - Fangpeng Lu; Songyan Liu; Wenbin Lu; Peng Chen; Boyang Ding (IEEE Access, 2025)

Student behavior detection model based on multilevel residual networks and hybrid attention mechanisms. - Wenbin Lu; Songyan Liu; Boyang Ding; Peng Chen; Fangpeng Lu (Neurocomputing, 2025)

Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event Data. - Sehwan Kim; Rui Wang; Wenbin Lu (CoRR, 2025)

Off-Policy Evaluation Under Nonignorable Missing Data. - Han Wang; Yang Xu; Wenbin Lu; Rui Song 006 (CoRR, 2025)