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2020 – today
- 2023
[i32]Xihaier Luo, Sean McCorkle, Gilchan Park, Vanessa López-Marrero, Shinjae Yoo, Edward R. Dougherty, Xiaoning Qian, Francis J. Alexander, Byung-Jun Yoon:
Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response. CoRR abs/2301.01769 (2023)- [i31]Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji:
A Latent Diffusion Model for Protein Structure Generation. CoRR abs/2305.04120 (2023) - 2022
- [j80]Omar Maddouri
, Xiaoning Qian, Byung-Jun Yoon:
Deep graph representations embed network information for robust disease marker identification. Bioinform. 38(4): 1075-1086 (2022) - [j79]Omar Maddouri, Xiaoning Qian, Francis J. Alexander, Edward R. Dougherty, Byung-Jun Yoon:
Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning. Patterns 3(3): 100428 (2022) - [c84]Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian:
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition. AISTATS 2022: 1359-1379 - [c83]Xihaier Luo, Sean McCorkle, Gilchan Park, Vanessa López-Marrero, Shinjae Yoo, Edward R. Dougherty, Xiaoning Qian, Francis J. Alexander, Byung-Jun Yoon:
Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response. BIBM 2022: 2366-2374 - [c82]Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi:
Dynimp: Dynamic Imputation for Wearable Sensing Data through Sensory and Temporal Relatedness. ICASSP 2022: 3988-3992 - [c81]Mingzhou Fan, Byung-Jun Yoon, Francis J. Alexander, Edward R. Dougherty, Xiaoning Qian:
Adaptive Group Testing with Mismatched Models. ICASSP 2022: 4533-4537 - [c80]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian:
MoReL: Multi-omics Relational Learning. ICLR 2022 - [c79]Randy Ardywibowo, Zepeng Huo, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian:
VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty. ICML 2022: 865-877 - [c78]Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi:
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data. MLHC 2022: 101-122 - [c77]Yucheng Wang, Mengmeng Gu, Mingyuan Zhou, Xiaoning Qian:
Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture. SenSys 2022: 1109-1115 - [i30]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian:
MoReL: Multi-omics Relational Learning. CoRR abs/2203.08149 (2022) - [i29]Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian:
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition. CoRR abs/2204.00130 (2022) - [i28]Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak Mortazavi:
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data. CoRR abs/2207.11382 (2022) - [i27]Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi:
DynImp: Dynamic Imputation for Wearable Sensing Data Through Sensory and Temporal Relatedness. CoRR abs/2209.15415 (2022) - 2021
- [j78]Byung-Jun Yoon, Xiaoning Qian, Edward R. Dougherty:
Quantifying the Multi-Objective Cost of Uncertainty. IEEE Access 9: 80351-80359 (2021) - [j77]Shahin Boluki, Xiaoning Qian, Edward R. Dougherty:
Optimal Bayesian supervised domain adaptation for RNA sequencing data. Bioinform. 37(19): 3212-3219 (2021) - [j76]Ameer Hamza Shakur, Shuai Huang, Xiaoning Qian, Xiangyu Chang:
SURVFIT: Doubly sparse rule learning for survival data. J. Biomed. Informatics 117: 103691 (2021) - [j75]Xuan Dang, Shuai Huang, Xiaoning Qian:
Risk Factor Identification in Heterogeneous Disease Progression with L1-Regularized Multi-state Models. J. Heal. Informatics Res. 5(1): 20-53 (2021) - [j74]Xuan Dang, Shuai Huang, Xiaoning Qian:
Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors. Stat. Comput. 31(6): 77 (2021) - [j73]Alireza Karbalayghareh, Xiaoning Qian, Edward R. Dougherty:
Optimal Bayesian Transfer Learning for Count Data. IEEE ACM Trans. Comput. Biol. Bioinform. 18(2): 644-655 (2021) - [c76]Ziyu Xiang, Mingzhou Fan, Guillermo Vázquez Tovar, William Trehern, Byung-Jun Yoon, Xiaofeng Qian, Raymundo Arróyave, Xiaoning Qian:
Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science. AAAI 2021: 10414-10421 - [c75]Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian:
Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty. AISTATS 2021: 3970-3978 - [c74]Zepeng Huo, Lida Zhang, Rohan Khera, Shuai Huang, Xiaoning Qian, Zhangyang Wang, Bobak J. Mortazavi:
Sparse Gated Mixture-of-Experts to Separate and Interpret Patient Heterogeneity in EHR data. BHI 2021: 1-4 - [c73]Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou:
Contextual Dropout: An Efficient Sample-Dependent Dropout Module. ICLR 2021 - [c72]Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian:
Uncertainty-aware Active Learning for Optimal Bayesian Classifier. ICLR 2021 - [c71]Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian:
Efficient Active Learning for Gaussian Process Classification by Error Reduction. NeurIPS 2021: 9734-9746 - [i26]Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou:
Contextual Dropout: An Efficient Sample-Dependent Dropout Module. CoRR abs/2103.04181 (2021) - [i25]Omar Maddouri, Xiaoning Qian, Byung-Jun Yoon:
Geometric Affinity Propagation for Clustering with Network Knowledge. CoRR abs/2103.14376 (2021) - [i24]Omar Maddouri, Xiaoning Qian, Francis J. Alexander, Edward R. Dougherty, Byung-Jun Yoon:
Robust Importance Sampling for Error Estimation in the Context of Optimal Bayesian Transfer Learning. CoRR abs/2109.02150 (2021) - [i23]Hyun-Myung Woo, Xiaoning Qian, Li Tan, Shantenu Jha, Francis J. Alexander, Edward R. Dougherty, Byung-Jun Yoon:
Optimal Decision Making in High-Throughput Virtual Screening Pipelines. CoRR abs/2109.11683 (2021) - [i22]Seyednami Niyakan, Xiaoning Qian:
COVID-Datathon: Biomarker identification for COVID-19 severity based on BALF scRNA-seq data. CoRR abs/2110.04986 (2021) - 2020
- [j72]Yijie Wang, Hyundoo Jeong, Byung-Jun Yoon, Xiaoning Qian:
ClusterM: a scalable algorithm for computational prediction of conserved protein complexes across multiple protein interaction networks. BMC Genom. 21(S-10) (2020) - [j71]Meltem Apaydin, Liang Xu, Bo Zeng, Xiaoning Qian:
Pessimistic optimisation for modelling microbial communities with uncertainty. Int. J. Comput. Biol. Drug Des. 13(1): 82-97 (2020) - [j70]Chung-Chi Tsai, Kuang-Jui Hsu, Yen-Yu Lin, Xiaoning Qian, Yung-Yu Chuang:
Deep Co-Saliency Detection via Stacked Autoencoder-Enabled Fusion and Self-Trained CNNs. IEEE Trans. Multim. 22(4): 1016-1031 (2020) - [j69]Guang Zhao, Xiaoning Qian, Byung-Jun Yoon, Francis J. Alexander, Edward R. Dougherty:
Model-Based Robust Filtering and Experimental Design for Stochastic Differential Equation Systems. IEEE Trans. Signal Process. 68: 3849-3859 (2020) - [c70]Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi:
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. AISTATS 2020: 3894-3904 - [c69]Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Learnable Bernoulli Dropout for Bayesian Deep Learning. AISTATS 2020: 3905-3916 - [c68]Qing Jin, Linjie Yang, Zhenyu Liao, Xiaoning Qian:
Neural Network Quantization with Scale-Adjusted Training. BMVC 2020 - [c67]Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian:
Arsm Gradient Estimator for Supervised Learning to Rank. ICASSP 2020: 3157-3161 - [c66]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Stochastic Recurrent Neural Networks. ICASSP 2020: 3342-3346 - [c65]Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian:
NADS: Neural Architecture Distribution Search for Uncertainty Awareness. ICML 2020: 356-366 - [c64]Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
Bayesian Graph Neural Networks with Adaptive Connection Sampling. ICML 2020: 4094-4104 - [c63]Ameer Hamza Shakur, Xiaoning Qian, Zhangyang Wang, Bobak Mortazavi, Shuai Huang:
GPSRL: Learning Semi-Parametric Bayesian Survival Rule Lists from Heterogeneous Patient Data. ICPR 2020: 10608-10615 - [c62]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. NeurIPS 2020 - [c61]Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian:
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. UAI 2020: 540-549 - [i21]Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Learnable Bernoulli Dropout for Bayesian Deep Learning. CoRR abs/2002.05155 (2020) - [i20]Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi:
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. CoRR abs/2003.01753 (2020) - [i19]Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian:
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. CoRR abs/2005.10477 (2020) - [i18]Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
Bayesian Graph Neural Networks with Adaptive Connection Sampling. CoRR abs/2006.04064 (2020) - [i17]Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian:
NADS: Neural Architecture Distribution Search for Uncertainty Awareness. CoRR abs/2006.06646 (2020) - [i16]Byung-Jun Yoon, Xiaoning Qian, Edward R. Dougherty:
Quantifying the multi-objective cost of uncertainty. CoRR abs/2010.04653 (2020) - [i15]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Xiaoning Qian:
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. CoRR abs/2010.05895 (2020)
2010 – 2019
- 2019
- [j68]Shahin Boluki, Xiaoning Qian, Edward R. Dougherty:
Experimental Design via Generalized Mean Objective Cost of Uncertainty. IEEE Access 7: 2223-2230 (2019) - [j67]Chun-Chi Chen, Xiaoning Qian, Byung-Jun Yoon:
RNAdetect: efficient computational detection of novel non-coding RNAs. Bioinform. 35(7): 1133-1141 (2019) - [j66]Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Bayesian negative binomial regression for differential expression with confounding factors. Bioinform. 35(13): 2346 (2019) - [j65]Chun-Chi Chen, Hyundoo Jeong, Xiaoning Qian, Byung-Jun Yoon:
TOPAS: network-based structural alignment of RNA sequences. Bioinform. 35(17): 2941-2948 (2019) - [j64]Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci, Ranadip Pal:
Selected research articles from the 2018 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC). BMC Bioinform. 20-S(12): 316:1-316:3 (2019) - [j63]Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian, Edward R. Dougherty:
Optimal clustering with missing values. BMC Bioinform. 20-S(12): 321:1-321:10 (2019) - [j62]Kai He, Shuai Huang, Xiaoning Qian:
Early detection and risk assessment for chronic disease with irregular longitudinal data analysis. J. Biomed. Informatics 96 (2019) - [j61]Tianshu Feng, Xiaoning Qian, Kaibo Liu, Shuai Huang:
Dynamic Inspection of Latent Variables in State-Space Systems. IEEE Trans Autom. Sci. Eng. 16(3): 1232-1243 (2019) - [j60]Shahin Boluki, Mohammad Shahrokh Esfahani, Xiaoning Qian, Edward R. Dougherty:
Constructing Pathway-Based Priors within a Gaussian Mixture Model for Bayesian Regression and Classification. IEEE ACM Trans. Comput. Biol. Bioinform. 16(2): 524-537 (2019) - [j59]Chung-Chi Tsai, Weizhi Li, Kuang-Jui Hsu, Xiaoning Qian, Yen-Yu Lin:
Image Co-Saliency Detection and Co-Segmentation via Progressive Joint Optimization. IEEE Trans. Image Process. 28(1): 56-71 (2019) - [c60]Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian:
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models. AISTATS 2019: 266-275 - [c59]Wuyang Chen, Ziyu Jiang, Zhangyang Wang, Kexin Cui, Xiaoning Qian:
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images. CVPR 2019: 8924-8933 - [c58]Xiaoqian Jia, Sicheng Wang, Xiao Liang, Anjali Balagopal, Dan Nguyen, Ming Yang, Zhangyang Wang, Jim Xiuquan Ji, Xiaoning Qian, Steve B. Jiang:
Cone-Beam Computed Tomography (CBCT) Segmentation by Adversarial Learning Domain Adaptation. MICCAI (6) 2019: 567-575 - [c57]Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian:
Variational Graph Recurrent Neural Networks. NeurIPS 2019: 10700-10710 - [c56]Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Graph Variational Auto-Encoders. NeurIPS 2019: 10711-10722 - [i14]Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian:
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models. CoRR abs/1901.02427 (2019) - [i13]Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian, Edward R. Dougherty:
Optimal Clustering with Missing Values. CoRR abs/1902.09694 (2019) - [i12]Wuyang Chen, Ziyu Jiang, Zhangyang Wang, Kexin Cui, Xiaoning Qian:
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images. CoRR abs/1905.06368 (2019) - [i11]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Graph Variational Auto-Encoders. CoRR abs/1908.07078 (2019) - [i10]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Variational Graph Recurrent Neural Networks. CoRR abs/1908.09710 (2019) - [i9]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Stochastic Recurrent Neural Networks. CoRR abs/1910.12819 (2019) - [i8]Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian:
ARSM Gradient Estimator for Supervised Learning to Rank. CoRR abs/1911.00465 (2019) - 2018
- [j58]Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Covariate-dependent negative binomial factor analysis of RNA sequencing data. Bioinform. 34(13): i61-i69 (2018) - [j57]Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Bayesian negative binomial regression for differential expression with confounding factors. Bioinform. 34(19): 3349-3356 (2018) - [j56]Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci, Ranadip Pal:
Selected research articles from the 2017 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC). BMC Bioinform. 19-S(3): 69:1-69:4 (2018) - [j55]Roozbeh Dehghannasiri, Xiaoning Qian, Edward R. Dougherty:
A Bayesian robust Kalman smoothing framework for state-space models with uncertain noise statistics. EURASIP J. Adv. Signal Process. 2018: 55 (2018) - [j54]Randy Ardywibowo, Shuai Huang, Shupeng Gui, Cao Xiao, Yu Cheng, Ji Liu, Xiaoning Qian:
Switching-State Dynamical Modeling of Daily Behavioral Data. J. Heal. Informatics Res. 2(3): 228-247 (2018) - [j53]Shaogang Ren, Shuai Huang, Jieping Ye, Xiaoning Qian:
Safe Feature Screening for Generalized LASSO. IEEE Trans. Pattern Anal. Mach. Intell. 40(12): 2992-3006 (2018) - [j52]Xiaopeng Lucia Sui, Li Xu, Xiaoning Qian, Tie Liu:
Convex clustering with metric learning. Pattern Recognit. 81: 575-584 (2018) - [j51]Roozbeh Dehghannasiri, Xiaoning Qian, Edward R. Dougherty:
Intrinsically Bayesian robust Karhunen-Loève compression. Signal Process. 144: 311-322 (2018) - [j50]Alireza Karbalayghareh, Xiaoning Qian, Edward R. Dougherty:
Optimal Bayesian Transfer Regression. IEEE Signal Process. Lett. 25(11): 1655-1659 (2018) - [j49]Ying Lin, Kaibo Liu, Eunshin Byon, Xiaoning Qian, Shan Liu, Shuai Huang:
A Collaborative Learning Framework for Estimating Many Individualized Regression Models in a Heterogeneous Population. IEEE Trans. Reliab. 67(1): 328-341 (2018) - [j48]Roozbeh Dehghannasiri, Mohammad Shahrokh Esfahani, Xiaoning Qian, Edward R. Dougherty:
Optimal Bayesian Kalman Filtering With Prior Update. IEEE Trans. Signal Process. 66(8): 1982-1996 (2018) - [j47]Alireza Karbalayghareh, Xiaoning Qian, Edward R. Dougherty:
Optimal Bayesian Transfer Learning. IEEE Trans. Signal Process. 66(14): 3724-3739 (2018) - [j46]Siamak Zamani Dadaneh, Edward R. Dougherty, Xiaoning Qian:
Optimal Bayesian Classification With Missing Values. IEEE Trans. Signal Process. 66(16): 4182-4192 (2018) - [c55]Roozbeh Dehghannasiri, Xiaoning Qian, Edward R. Dougherty:
Robust Smoothing for State-Space Models with Unknown Noise Statistics. ACSSC 2018: 1024-1028 - [c54]Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian, Edward R. Dougherty:
Optimal Clustering with Missing Values. BCB 2018: 593-594 - [c53]Ehsan Hajiramezanali, Mahdi Imani, Ulisses M. Braga-Neto, Xiaoning Qian, Edward R. Dougherty:
Scalable Optimal Bayesian Classification of Single-Cell Trajectories under Regulatory Model Uncertainty. BCB 2018: 596-597 - [c52]Kuang-Jui Hsu, Chung-Chi Tsai, Yen-Yu Lin, Xiaoning Qian, Yung-Yu Chuang:
Unsupervised CNN-Based Co-saliency Detection with Graphical Optimization. ECCV (5) 2018: 502-518 - [c51]Yixin Fang, Ruoming Jin, Wei Xiong, Xiaoning Qian, Dejing Dou, Hai Phan:
Recursive Structure Similarity: A Novel Algorithm for Graph Clustering. ICTAI 2018: 395-400 - [c50]Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Alireza Karbalayghareh, Mingyuan Zhou, Xiaoning Qian:
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data. NeurIPS 2018: 9133-9142 - [i7]Alireza Karbalayghareh, Xiaoning Qian, Edward R. Dougherty:
Optimal Bayesian Transfer Learning. CoRR abs/1801.00857 (2018) - [i6]Shaogang Ren, Jianhua Z. Huang, Shuai Huang, Xiaoning Qian:
Safe Active Feature Selection for Sparse Learning. CoRR abs/1806.05817 (2018) - [i5]Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Alireza Karbalayghareh, Mingyuan Zhou, Xiaoning Qian:
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data. CoRR abs/1810.09433 (2018) - [i4]Guang Zhao, Raymundo Arróyave, Xiaoning Qian:
Fast Exact Computation of Expected HyperVolume Improvement. CoRR abs/1812.07692 (2018) - 2017
- [j45]Shahin Boluki, Mohammad Shahrokh Esfahani, Xiaoning Qian, Edward R. Dougherty:
Incorporating biological prior knowledge for Bayesian learning via maximal knowledge-driven information priors. BMC Bioinform. 18(14): 61-80 (2017) - [j44]Chun-Chi Chen, Xiaoning Qian, Byung-Jun Yoon:
Effective computational detection of piRNAs using n-gram models and support vector machine. BMC Bioinform. 18(14): 103-109 (2017) - [j43]Hyundoo Jeong, Xiaoning Qian, Byung-Jun Yoon:
CUFID-query: accurate network querying through random walk based network flow estimation. BMC Bioinform. 18(14): 133-146 (2017) - [j42]Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci:
Selected research articles from the 2016 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC). BMC Bioinform. 18(S-4): 1-3 (2017) - [j41]Yijie Wang, Xiaoning Qian:
Finding low-conductance sets with dense interactions (FLCD) for better protein complex prediction. BMC Syst. Biol. 11(3): 22:1-22:11 (2017) - [j40]Chun-Chi Chen, Noushin Ghaffari, Xiaoning Qian, Byung-Jun Yoon:
Optimal hybrid sequencing and assembly: Feasibility conditions for accurate genome reconstruction and cost minimization strategy. Comput. Biol. Chem. 69: 153-163 (2017) - [j39]Roozbeh Dehghannasiri, Xiaoning Qian, Edward R. Dougherty:
Optimal experimental design in the context of canonical expansions. IET Signal Process. 11(8): 942-951 (2017) - [j38]Chuyang Ke, Yan Jin, Heather L. Evans, Bill Lober, Xiaoning Qian, Ji Liu, Shuai Huang:
Prognostics of surgical site infections using dynamic health data. J. Biomed. Informatics 65: 22-33 (2017) - [j37]Yijun Huang, Qiang Meng, Heather L. Evans, William B. Lober, Yu Cheng, Xiaoning Qian, Ji Liu, Shuai Huang:
CHI: A contemporaneous health index for degenerative disease monitoring using longitudinal measurements. J. Biomed. Informatics 73: 115-124 (2017) - [j36]Amin Ahmadi Adl, Hye-Seung Lee, Xiaoning Qian:
Detecting Pairwise Interactive Effects of Continuous Random Variables for Biomarker Identification with Small Sample Size. IEEE ACM Trans. Comput. Biol. Bioinform. 14(6): 1265-1275 (2017) - [j35]Easton Li Xu, Xiaoning Qian, Tie Liu, Shuguang Cui:
Detection of Cooperative Interactions in Logistic Regression Models. IEEE Trans. Signal Process. 65(7): 1765-1780 (2017) - [c49]Roozbeh Dehghannasiri, Mohammad Shahrokh Esfahani, Xiaoning Qian, Edward R. Dougherty:
Bayesian Kalman filtering in the presence of unknown noise statistics using factor graphs. ACSSC 2017: 166-170 - [c48]Roozbeh Dehghannasiri, Xiaoning Qian, Edward R. Dougherty:
An objective-based experimental design framework for signal processing in the context of canonical expansions. ACSSC 2017: 789-793 - [c47]Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci:
CNB-MAC'17: The Fourth International Workshop on Computational Network Biology: Modeling, Analysis, and Control. BCB 2017: 750 - [c46]Easton Li Xu, Xiaoning Qian, Qilian Yu, Han Zhang, Shuguang Cui:
Feature Selection with Interactions in Logistic Regression Models using Multivariate Synergies for a GWAS Application. BCB 2017: 760-761 - [c45]Chung-Chi Tsai, Xiaoning Qian, Yen-Yu Lin:
Image co-saliency detection via locally adaptive saliency map fusion. ICASSP 2017: 1897-1901 - [c44]Weizhi Li, Xiaoning Qian, Jim Jing-Yan Ji:
Noise-tolerant deep learning for histopathological image segmentation. ICIP 2017: 3075-3079 - [c43]Chung-Chi Tsai, Xiaoning Qian, Yen-Yu Lin:
Segmentation guided local proposal fusion for co-saliency detection. ICME 2017: 523-528 - 2016
- [j34]Hyundoo Jeong, Xiaoning Qian, Byung-Jun Yoon:
Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model. BMC Bioinform. 17(S-13): 395 (2016) - [j33]