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2020 – today
- 2024
[j21]Chang Su
, Yu Hou, Jielin Xu, Zhenxing Xu, Manqi Zhou, Alison Ke, Haoyang Li, Jie Xu, Matthew Brendel, Jacqueline R. M. A. Maasch, Zilong Bai, Haotan Zhang, Yingying Zhu, Molly C. Cincotta, Xinghua Shi, Claire Henchcliffe, James B. Leverenz, Jeffrey Cummings, Michael S. Okun, Jiang Bian, Feixiong Cheng, Fei Wang:
Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data. npj Digit. Medicine 7(1) (2024)- [j20]Xinliang Wei, Kejiang Ye, Xinghua Shi, Cheng-Zhong Xu, Yu Wang:
Joint Participant and Learning Topology Selection for Federated Learning in Edge Clouds. IEEE Trans. Parallel Distributed Syst. 35(8): 1456-1468 (2024) - [c33]Junjie Chen, Jiahao Li, Chen Song, Bin Li, Qingcai Chen, Hongchang Gao, Wendy Hui Wang, Zenglin Xu, Xinghua Shi:
Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks. AAAI 2024: 11338-11345 - [c32]Chen Song, Wenkang Zhan, Xinghua Shi:
SparseHE: An Efficient Privacy-Preserving Biomedical Prediction Approach Using Sparse Homomorphic Encryption. ICHI 2024: 103-112 - 2023
- [c31]Xinghua Shi, Jia Feng, Fan Zhang, Chuangxin Guo:
Multi-Energy Coordinated Day-ahead Energy Management of Integrated Electrical-Gas Energy System. IoTAAI 2023: 434-438 - [i2]Yihan Zhang, Wenhao Jiang, Feng Zheng, Chiu C. Tan, Xinghua Shi, Hongchang Gao:
Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems? CoRR abs/2304.11788 (2023) - 2022
- [j19]Meng Song, Jonathan Greenbaum, Joseph Luttrell IV, Weihua Zhou, Chong Wu, Zhe Luo, Chuan Qiu, Lan Juan Zhao, Kuan-Jui Su, Qing Tian, Hui Shen, Huixiao Hong, Ping Gong, Xinghua Shi, Hong-Wen Deng, Chaoyang Zhang:
An autoencoder-based deep learning method for genotype imputation. Frontiers Artif. Intell. 5 (2022) - [c30]Supratim Das, Xinghua Shi:
Offspring GAN augments biased human genomic data. BCB 2022: 50:1-50:10 - [c29]Xinliang Wei, Jiyao Liu, Xinghua Shi, Yu Wang:
Participant Selection for Hierarchical Federated Learning in Edge Clouds. NAS 2022: 1-8 - [e2]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] - 2021
- [j18]Min Li, Yake Wang, Ruiqing Zheng, Xinghua Shi, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines. IEEE ACM Trans. Comput. Biol. Bioinform. 18(2): 575-582 (2021) - [j17]Ting Li, Zhijin Qiu, Lijuan Cao, Dazhao Cheng, Weichao Wang, Xinghua Shi, Yu Wang:
Privacy-Preserving Participant Grouping for Mobile Social Sensing Over Edge Clouds. IEEE Trans. Netw. Sci. Eng. 8(2): 865-880 (2021) - [c28]Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi:
On the Convergence of Stochastic Compositional Gradient Descent Ascent Method. IJCAI 2021: 2389-2395 - [c27]Junjie Chen, Wendy Hui Wang, Hongchang Gao, Xinghua Shi:
PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks. KDD 2021: 127-137 - [c26]Junjie Chen, Wendy Hui Wang, Xinghua Shi:
Differential Privacy Protection Against Membership Inference Attack on Machine Learning for Genomic Data. PSB 2021 - 2020
- [j16]Jia Wen, Colby T. Ford, Daniel Janies, Xinghua Shi:
A parallelized strategy for epistasis analysis based on Empirical Bayesian Elastic Net models. Bioinform. 36(12): 3803-3810 (2020) - [j15]Yan Guo, Li Shen, Xinghua Shi, Kai Wang, Yulin Dai, Zhongming Zhao:
Accelerating bioinformatics research with International Conference on Intelligent Biology and Medicine 2020. BMC Bioinform. 21-S(21): 563 (2020) - [j14]Li Shen, Xinghua Shi, Zhongming Zhao, Kai Wang:
Informatics and machine learning methods for health applications. BMC Medical Informatics Decis. Mak. 20-S(11): 342 (2020) - [c25]Junjie Chen, Mohammad Erfan Mowlaei, Xinghua Shi:
Population-scale Genomic Data Augmentation Based on Conditional Generative Adversarial Networks. BCB 2020: 26:1-26:6
2010 – 2019
- 2019
- [j13]Lu Zhang, Qiuping Pan, Yue Wang, Xintao Wu, Xinghua Shi:
Bayesian Network Construction and Genotype-Phenotype Inference Using GWAS Statistics. IEEE ACM Trans. Comput. Biol. Bioinform. 16(2): 475-489 (2019) - [c24]Junjie Chen, Xinghua Shi:
A Sparse Convolutional Predictor with Denoising Autoencoders for Phenotype Prediction. BCB 2019: 217-222 - [c23]Xinghua Shi, Jinxuan Cao, Tianliang Lu, Victor Chang:
A Survey on RFID Security and Privacy in Smart Medical: Threats and Protections. IoTBDS 2019: 278-285 - [e1]Xinghua Mindy Shi, Michael Buck, Jian Ma, Pierangelo Veltri:
Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2019, Niagara Falls, NY, USA, September 7-10, 2019. ACM 2019, ISBN 978-1-4503-6666-3 [contents] - 2018
- [j12]Zaixiang Tang, Yueping Shen, Yan Li, Xinyan Zhang, Jia Wen, Chen'ao Qian, Wenzhuo Zhuang, Xinghua Shi, Nengjun Yi:
Group spike-and-slab lasso generalized linear models for disease prediction and associated genes detection by incorporating pathway information. Bioinform. 34(6): 901-910 (2018) - [c22]Yake Wang, Min Li, Ruiqing Zheng, Xinghua Shi, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
Using Deep Neural Network to Predict Drug Sensitivity of Cancer Cell Lines. ICIC (2) 2018: 223-226 - [c21]Ting Li, Zhijin Qiu, Lijuan Cao, Hanshang Li, Zhongwen Guo, Fan Li, Xinghua Shi, Yu Wang:
Participant Grouping for Privacy Preservation in Mobile Crowdsensing over Hierarchical Edge Clouds. IPCCC 2018: 1-8 - 2017
- [j11]Zhiyong Wang, Benika Hall, Jinbo Xu, Xinghua Shi:
A Sparse Learning Framework for Joint Effect Analysis of Copy Number Variants. IEEE ACM Trans. Comput. Biol. Bioinform. 14(5): 1013-1027 (2017) - [j10]Shaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi:
Nonparametric Detection of Anomalous Data Streams. IEEE Trans. Signal Process. 65(21): 5785-5797 (2017) - [c20]Andrew Quitadamo, James Johnson, Xinghua Shi:
Bayesian Hyperparameter Optimization for Machine Learning Based eQTL Analysis. BCB 2017: 98-106 - [c19]Penglin Dong, Weichao Wang, Xinghua Shi, Tuanfa Qin:
Lightweight Key Management for Group Communication in Body Area Networks through Physical Unclonable Functions. CHASE 2017: 102-107 - [c18]Liping Xie, Weichao Wang, Xinghua Shi, Tuanfa Qin:
Lightweight mutual authentication among sensors in body area networks through Physical Unclonable Functions. ICC 2017: 1-6 - 2016
- [c17]Lu Zhang, Qiuping Pan, Xintao Wu, Xinghua Shi:
Building Bayesian networks from GWAS statistics based on Independence of Causal Influence. BIBM 2016: 529-532 - [c16]Rui Xie, Andrew Quitadamo, Jianlin Cheng, Xinghua Shi:
A predictive model of gene expression using a deep learning framework. BIBM 2016: 676-681 - [c15]Yue Wang, Jia Wen, Xintao Wu, Xinghua Shi:
Infringement of Individual Privacy via Mining Differentially Private GWAS Statistics. BigCom 2016: 355-366 - 2015
- [j9]Andrew Quitadamo, Lu Tian, Benika Hall, Xinghua Shi:
An integrated network of microRNA and gene expression in ovarian cancer. BMC Bioinform. 16(S-5): S5 (2015) - [c14]Anhong He, Benika Hall, Jia Wen, Yingbin Liang, Xinghua Shi:
Sequential parallel LASSO models for eQTL analysis. BCB 2015: 533-534 - [c13]Benika Hall, Andrew Quitadamo, Xinghua Shi:
A Graph Community Approach for Constructing microRNA Networks. BigCom 2015: 283-293 - 2014
- [j8]Zhiyong Wang, Jinbo Xu, Xinghua Shi:
Finding Alternative Expression Quantitative Trait Loci by Exploring Sparse Model Space. J. Comput. Biol. 21(5): 385-393 (2014) - [c12]Shaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi:
Unsupervised nonparametric anomaly detection: A kernel method. Allerton 2014: 836-841 - [c11]Zhiyong Wang, Jinbo Xu, Xinghua Shi:
CNVnet: combining sparse learning and biological networks to capture joint effect of copy number variants. BCB 2014: 128-137 - [c10]Shaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi:
Kernel-based nonparametric anomaly detection. SPAWC 2014: 224-228 - [i1]Shaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi:
Nonparametric Detection of Anomalous Data via Kernel Mean Embedding. CoRR abs/1405.2294 (2014) - 2013
- [j7]Ying Zhu, Bin Xu, Xinghua Shi, Yu Wang:
A Survey of Social-Based Routing in Delay Tolerant Networks: Positive and Negative Social Effects. IEEE Commun. Surv. Tutorials 15(1): 387-401 (2013) - [c9]Yue Wang, Xintao Wu, Xinghua Shi:
Using aggregate human genome data for individual identification. BIBM 2013: 410-415 - 2012
- [j6]Xinghua Shi, Yimin Wei:
A sharp version of Bauer-Fike's theorem. J. Comput. Appl. Math. 236(13): 3218-3227 (2012) - [j5]Dingbang Xu, Yu Wang, Xinghua Shi, Xiaohang Yin:
User identification and anonymization in 802.11 wireless LANs. Secur. Commun. Networks 5(1): 15-27 (2012) - [c8]Xiaohui Chen, Xinghua Shi, Xing Xu, Zhiyong Wang, Ryan Mills, Charles Lee, Jinbo Xu:
A Two-Graph Guided Multi-task Lasso Approach for eQTL Mapping. AISTATS 2012: 208-217 - 2011
- [j4]Xinghua Shi, Yimin Wei, Wen Zhang:
Convergence of General Nonstationary Iterative Methods for Solving Singular Linear Equations. SIAM J. Matrix Anal. Appl. 32(1): 72-89 (2011) - [j3]Siyuan Chen, Yu Wang, Xiang-Yang Li, Xinghua Shi:
Capacity of data collection in randomly-deployed wireless sensor networks. Wirel. Networks 17(2): 305-318 (2011) - 2010
- [c7]Dingbang Xu, Yu Wang, Xinghua Shi, Xiaohang Yin:
802.11 User Anonymization. GLOBECOM 2010: 1-5
2000 – 2009
- 2009
- [j2]Yu Wang, Lijuan Cao, Teresa A. Dahlberg, Fan Li, Xinghua Shi:
Self-organizing fault-tolerant topology control in large-scale three-dimensional wireless networks. ACM Trans. Auton. Adapt. Syst. 4(3): 19:1-19:21 (2009) - [c6]Xinghua Shi, Rick L. Stevens:
A Bayesian Approach to High-Throughput Biological Model Generation. BICoB 2009: 376-387 - [c5]Siyuan Chen, Yu Wang, Xiang-Yang Li, Xinghua Shi:
Data Collection Capacity of Random-Deployed Wireless Sensor Networks. GLOBECOM 2009: 1-6 - [c4]Dingbang Xu, Yu Wang, Xinghua Shi:
Enhanced Feature Selection and Generation for 802.11 User Identification. ICCCN 2009: 1-6 - [c3]Siyuan Chen, Yu Wang, Xiang-Yang Li, Xinghua Shi:
Order-Optimal Data Collection in Wireless Sensor Networks: Delay and Capacity. SECON 2009: 1-9 - 2008
- [c2]Xinghua Shi, Rick Stevens:
SWARM: a scientific workflow for supporting bayesian approaches to improve metabolic models. CLADE 2008: 25-34 - 2007
- [j1]Leslie Klis McNeil, Claudia Reich, Ramy K. Aziz, Daniela Bartels, Matthew Cohoon, Terry Disz, Robert A. Edwards, Svetlana Gerdes, Kaitlyn Hwang, Michael Kubal, Gohar Rem Margaryan, Folker Meyer, William Mihalo, Gary J. Olsen, Robert Olson, Andrei Osterman, Daniel Paarmann, Tobias Paczian, Bruce D. Parrello, Gordon D. Pusch, Dmitry A. Rodionov, Xinghua Shi, Olga Vassieva, Veronika Vonstein, Olga Zagnitko, Fangfang Xia, Jenifer Zinner, Ross A. Overbeek, Rick Stevens:
The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation. Nucleic Acids Res. 35(Database-Issue): 347-353 (2007) - 2005
- [c1]Yu Wang, Xinghua Shi:
Efficient on-demand topology control for wireless ad hoc networks. ICCCN 2005: 159-164
Coauthor Index
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last updated on 2024-11-14 00:54 CET by the dblp team
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