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2020 – today
- 2023
[j22]Jingxuan Bao
, Changgee Chang, Qiyiwen Zhang, Andrew J. Saykin, Li Shen, Qi Long:
Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis. Briefings Bioinform. 24(2) (2023)- [j21]Emily J. Getzen, Lyle H. Ungar, Danielle Mowery, Xiaoqian Jiang, Qi Long:
Mining for equitable health: Assessing the impact of missing data in electronic health records. J. Biomed. Informatics 139: 104269 (2023) - [j20]Amelia L. M. Tan, Emily J. Getzen, Meghan R. Hutch, Zachary H. Strasser, Alba Gutiérrez-Sacristán, Trang T. Le, Arianna Dagliati, Michele Morris, David A. Hanauer, Bertrand Moal, Clara-Lea Bonzel, William Yuan, Lorenzo Chiudinelli, Priam Das, Harrison G. Zhang, Bruce J. Aronow, Paul Avillach, Gabriel A. Brat, Tianxi Cai, Chuan Hong, William G. La Cava, He Hooi Will Loh, Yuan Luo, Shawn N. Murphy, Kee Yuan Hgiam, Gilbert S. Omenn, Lav P. Patel, Malarkodi J. Samayamuthu, Emily R. Shriver, Zahra Shakeri Hossein Abad, Byorn W. L. Tan, Shyam Visweswaran, Xuan Wang, Griffin M. Weber, Zongqi Xia, Bertrand Verdy, Qi Long, Danielle L. Mowery, John H. Holmes:
Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record? J. Biomed. Informatics 139: 104306 (2023) - [j19]Kan Chen, Siyu Heng, Qi Long, Bo Zhang:
Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies. J. Comput. Graph. Stat. 32(2): 528-538 (2023) - [j18]Qi Long, Fei Wang, Wenyan Ge, Feng Jiao, Jianqiao Han, Hao Chen, Fidel Alejandro Roig, Elena María Abraham, Mengxia Xie, Lu Cai:
Temporal and Spatial Change in Vegetation and Its Interaction with Climate Change in Argentina from 1982 to 2015. Remote. Sens. 15(7): 1926 (2023) - [j17]Changgee Chang, Zongyu Dai, Jihwan Oh, Qi Long:
Integrative learning of structured high-dimensional data from multiple datasets. Stat. Anal. Data Min. 16(2): 120-134 (2023) - [c21]Zhiqi Bu, Zongyu Dai, Yiliang Zhang, Qi Long:
MISNN: Multiple Imputation via Semi-parametric Neural Networks. PAKDD (1) 2023: 430-442 - [c20]Davoud Ataee Tarzanagh, Bojian Hou, Boning Tong, Qi Long, Li Shen:
Fairness-aware class imbalanced learning on multiple subgroups. UAI 2023: 2123-2133 - [i15]Zhiqi Bu, Zongyu Dai, Yiliang Zhang, Qi Long:
MISNN: Multiple Imputation via Semi-parametric Neural Networks. CoRR abs/2305.01794 (2023) - 2022
- [j16]Chong Jin, Brian Lee, Li Shen, Qi Long:
Integrating multi-omics summary data using a Mendelian randomization framework. Briefings Bioinform. 23(6) (2022) - [j15]Yixue Feng, Mansu Kim, Xiaohui Yao, Kefei Liu, Qi Long, Li Shen:
Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment. BMC Bioinform. 23-S(3): 402 (2022) - [j14]Mansu Kim, Eun Jeong Min, Kefei Liu, Jingwen Yan, Andrew J. Saykin, Jason H. Moore, Qi Long, Li Shen:
Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics. Medical Image Anal. 76: 102297 (2022) - [j13]Yingchun Li, Qi Long, Zhongjie Wu, Zhiquan Zhou:
Low-Complexity Joint 3D Super-Resolution Estimation of Range Velocity and Angle of Multi-Targets Based on FMCW Radar. Sensors 22(17): 6474 (2022) - [c19]Zongyu Dai, Zhiqi Bu, Qi Long:
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data. ACML 2022: 265-279 - [c18]Jiahang Sha, Jingxuan Bao, Kefei Liu, Shu Yang, Zixuan Wen, Yuhan Cui, Junhao Wen, Christos Davatzikos, Jason H. Moore, Andrew J. Saykin, Qi Long, Li Shen:
Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer's Disease. BIBM 2022: 541-548 - [c17]Qiyiwen Zhang, Zhiqi Bu, Kan Chen, Qi Long:
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability. ECML/PKDD (4) 2022: 604-619 - [e1]Donald A. Adjeroh, Qi Long, Xinghua Mindy Shi, Fei Guo, Xiaohua Hu, Srinivas Aluru, Giri Narasimhan, Jianxin Wang, Mingon Kang, Ananda Mondal, Jin Liu:
IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, Las Vegas, NV, USA, December 6-8, 2022. IEEE 2022, ISBN 978-1-6654-6819-0 [contents] - [i14]Kan Chen, Qishuo Yin, Qi Long:
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation. CoRR abs/2203.03185 (2022) - [i13]Zongyu Dai, Zhiqi Bu, Qi Long:
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data. CoRR abs/2211.13297 (2022) - 2021
- [c16]Qinqing Zheng, Shuxiao Chen, Qi Long, Weijie J. Su:
Federated f-Differential Privacy. AISTATS 2021: 2251-2259 - [c15]Mansu Kim, Jaesik Kim, Jeffrey Qu, Heng Huang, Qi Long, Kyung-Ah Sohn, Dokyoon Kim, Li Shen:
Interpretable temporal graph neural network for prognostic prediction of Alzheimer's disease using longitudinal neuroimaging data. BIBM 2021: 1381-1384 - [c14]Wenli Sun, Changgee Chang, Qi Long:
Graph-guided Bayesian SVM with Adaptive Structured Shrinkage Prior for High-dimensional Data. IEEE BigData 2021: 4472-4479 - [c13]Zongyu Dai, Zhiqi Bu, Qi Long:
Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems. ICMLA 2021: 791-798 - [c12]Yiliang Zhang, Qi Long:
Assessing Fairness in the Presence of Missing Data. NeurIPS 2021: 16007-16019 - [i12]Cong Fang, Hangfeng He, Qi Long, Weijie J. Su:
Layer-Peeled Model: Toward Understanding Well-Trained Deep Neural Networks. CoRR abs/2101.12699 (2021) - [i11]Qinqing Zheng, Shuxiao Chen, Qi Long, Weijie J. Su:
Federated $f$-Differential Privacy. CoRR abs/2102.11158 (2021) - [i10]Shuxiao Chen, Qinqing Zheng, Qi Long, Weijie J. Su:
A Theorem of the Alternative for Personalized Federated Learning. CoRR abs/2103.01901 (2021) - [i9]Zhiqi Bu, Hua Wang, Qi Long, Weijie J. Su:
On the Convergence of Deep Learning with Differential Privacy. CoRR abs/2106.07830 (2021) - [i8]Qiyiwen Zhang, Zhiqi Bu, Kan Chen, Qi Long:
Differentially Private Bayesian Neural Networks on Accuracy, Privacy and Reliability. CoRR abs/2107.08461 (2021) - [i7]Yiliang Zhang, Qi Long:
Fairness in Missing Data Imputation. CoRR abs/2110.12002 (2021) - [i6]Yiliang Zhang, Qi Long:
Assessing Fairness in the Presence of Missing Data. CoRR abs/2112.04899 (2021) - [i5]Zongyu Dai, Zhiqi Bu, Qi Long:
Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems. CoRR abs/2112.11507 (2021) - 2020
- [j12]Eun Jeong Min, Qi Long:
Sparse multiple co-Inertia analysis with application to integrative analysis of multi -Omics data. BMC Bioinform. 21(1): 141 (2020) - [c11]Yi Deng, Xiaoqian Jiang, Qi Long:
Privacy-Preserving Methods for Vertically Partitioned Incomplete Data. AMIA 2020 - [c10]Yingxuan Eng, Xiaohui Yao, Kefei Liu, Shannon L. Risacher, Andrew J. Saykin, Qi Long, Yize Zhao, Li Shen:
Polygenic mediation analysis of Alzheimer's disease implicated intermediate amyloid imaging phenotypes. AMIA 2020 - [c9]Yixue Feng, Mansu Kim, Xiaohui Yao, Kefei Liu, Qi Long, Li Shen:
Deep Multiview Learning to Identify Population Structure with Multimodal Imaging. BIBE 2020: 308-314 - [c8]Wenli Sun, Changgee Chang, Qi Long:
Joint Bayesian Variable Selection and Graph Estimation for Non-linear SVM with Application to Genomics Data. DSAA 2020: 315-323 - [c7]Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie J. Su:
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. ICML 2020: 11420-11435 - [c6]Changgee Chang, Jihwan Oh, Qi Long:
GRIA: Graphical Regularization for Integrative Analysis. SDM 2020: 604-612 - [i4]Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie J. Su:
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. CoRR abs/2003.04493 (2020) - [i3]Kefei Liu, Qi Long, Li Shen:
Grouping effects of sparse CCA models in variable selection. CoRR abs/2008.03392 (2020) - [i2]Yi Deng, Xiaoqian Jiang, Qi Long:
Privacy-Preserving Methods for Vertically Partitioned Incomplete Data. CoRR abs/2012.14954 (2020)
2010 – 2019
- 2019
- [j11]Eun Jeong Min, Sandra E. Safo, Qi Long:
Penalized co-inertia analysis with applications to -omics data. Bioinform. 35(6): 1018-1025 (2019) - [j10]Ziyi Li, Kirk Roberts, Xiaoqian Jiang, Qi Long:
Distributed learning from multiple EHR databases: Contextual embedding models for medical events. J. Biomed. Informatics 92 (2019) - [j9]Vu Viet Hoang Pham, Lin Liu, Cameron Bracken, Gregory J. Goodall, Qi Long, Jiuyong Li, Thuc Duy Le:
CBNA: A control theory based method for identifying coding and non-coding cancer drivers. PLoS Comput. Biol. 15(12) (2019) - [j8]Sandra E. Safo, Qi Long:
Sparse linear discriminant analysis in structured covariates space. Stat. Anal. Data Min. 12(2): 56-69 (2019) - [c5]Wenli Sun, Changgee Chang, Qi Long:
Bayesian Non-linear Support Vector Machine for High-Dimensional Data with Incorporation of Graph Information on Features. IEEE BigData 2019: 4874-4882 - [c4]Changgee Chang, Eun Jeong Min, Jihwan Oh, Qi Long:
Knowledge-Guided Biclustering via Sparse Variational EM Algorithm. ICBK 2019: 25-32 - [i1]Zhiqi Bu, Jinshuo Dong, Qi Long, Weijie J. Su:
Deep Learning with Gaussian Differential Privacy. CoRR abs/1911.11607 (2019) - 2018
- [j7]Sumyea Helal, Jiuyong Li, Lin Liu, Esmaeil Ebrahimie, Shane Dawson, Duncan J. Murray, Qi Long:
Predicting academic performance by considering student heterogeneity. Knowl. Based Syst. 161: 134-146 (2018) - [j6]Yize Zhao, Jian Kang, Qi Long:
Bayesian Multiresolution Variable Selection for Ultra-High Dimensional Neuroimaging Data. IEEE ACM Trans. Comput. Biol. Bioinform. 15(2): 537-550 (2018) - [c3]Wenli Sun, Changgee Chang, Yize Zhao, Qi Long:
Knowledge-Guided Bayesian Support Vector Machine for High-Dimensional Data with Application to Analysis of Genomics Data. IEEE BigData 2018: 1484-1493 - [c2]Eun Jeong Min, Changgee Chang, Qi Long:
Generalized Bayesian Factor Analysis for Integrative Clustering with Applications to Multi-Omics Data. DSAA 2018: 109-119 - 2017
- [j5]Ziyi Li, Sandra E. Safo, Qi Long:
Incorporating biological information in sparse principal component analysis with application to genomic data. BMC Bioinform. 18(1): 332 (2017) - [j4]Sara M. Clifton, Chaeryon Kang, Jingyi Jessica Li, Qi Long, Nirmish Shah, Daniel M. Abrams:
Hybrid Statistical and Mechanistic Mathematical Model Guides Mobile Health Intervention for Chronic Pain. J. Comput. Biol. 24(7): 675-688 (2017) - 2016
- [c1]Sandra E. Safo, Qi Long:
Sparse Linear Discriminant Analysis in Structured Covariates Space. DSAA 2016: 772-781 - 2013
- [j3]Matthias Chung, Qi Long, Brent A. Johnson:
A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems. Stat. Comput. 23(5): 601-614 (2013)
2000 – 2009
- 2009
- [j2]Qi Long, Qi-Ru Wang:
New oscillation criteria of second-order nonlinear differential equations. Appl. Math. Comput. 212(2): 357-365 (2009) - [j1]Ruijiang Wang, Yihong Ru, Qi Long:
Improved Adaptive and Multi-group Parallel Genetic Algorithm Based on Good-point Set. J. Softw. 4(4): 348-356 (2009)
Coauthor Index
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last updated on 2023-09-08 13:26 CEST by the dblp team
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