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2020 – today
- 2023
[j85]Puhua Niu
, Maria J. Soto, Shuai Huang, Byung-Jun Yoon, Edward R. Dougherty, Francis J. Alexander, Ian Blaby, Xiaoning Qian:
Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction. J. Comput. Biol. 30(7): 751-765 (2023)- [j84]Xiaoning Qian, Byung-Jun Yoon, Raymundo Arróyave, Xiaofeng Qian, Edward R. Dougherty:
Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery. Patterns 4(11): 100863 (2023) - [j83]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. Patterns 4(11): 100875 (2023) - [j82]Francis J. Alexander, Meifeng Lin, Xiaoning Qian, Byung-Jun Yoon:
Accelerating scientific discoveries through data-driven innovations. Patterns 4(11): 100876 (2023) - [j81]Omar Maddouri, Xiaoning Qian, Byung-Jun Yoon:
Geometric Affinity Propagation for Clustering With Network Knowledge. IEEE Trans. Knowl. Data Eng. 35(11): 11419-11436 (2023) - [c88]Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian:
Uncertainty-aware Unsupervised Video Hashing. AISTATS 2023: 6722-6740 - [c87]Alif Bin Abdul Qayyum, Xiaoning Qian, Byung-Jun Yoon:
Enhancing Cryo-EM Particle Picking Through Consistency Model-based Latent Space Denoiser. BCB 2023: 72:1 - [c86]Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji:
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. ICML 2023: 21260-21287 - [c85]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. ICML 2023: 40412-40424 - [i37]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) - [i36]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) - [i35]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. CoRR abs/2306.04922 (2023) - [i34]Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. CoRR abs/2306.09549 (2023) - [i33]Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji:
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. CoRR abs/2306.10045 (2023) - [i32]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i31]Sanket R. Jantre, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon:
Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks. CoRR abs/2309.03061 (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]