blank blank

    Heng Huang
    John A. Jurenko Endowed Professor
    Department of Electrical and Computer Engineering
    Department of Biomedical Informatics


Peer Reviewed Publications:

Guodong Liu, Hong Chen, Heng Huang. Sparse Shrunk Additive Models. Thirty-seventh International Conference on Machine Learning (ICML 2020), in press.

Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang. Momentum-Based Policy Gradient Methods. Thirty-seventh International Conference on Machine Learning (ICML 2020), in press.

Hongchang Gao, Heng Huang. Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems? Thirty-seventh International Conference on Machine Learning (ICML 2020), in press.

Lei Luo, Yanfu Zhang, Heng Huang. Adversarial Nonnegative Matrix Factorization. Thirty-seventh International Conference on Machine Learning (ICML 2020), in press.

Runxue Bao, Bin Gu, Heng Huang. Fast OSCAR and OWL with Safe Screening Rules. Thirty-seventh International Conference on Machine Learning (ICML 2020), in press.

Yangli-ao Geng, Qingyong Li, Tianyang Lin, Jing Zhang, Liangtao Xu, Dong Zheng, Wen Yao, Weitao Lyu, Heng Huang. A Heterogeneous Spatiotemporal Network for Lightning Prediction. IEEE International Conference on Data Mining (ICDM 2020), in press.

Jingwei Xin, NannanWang, Xinrui Jiang, Jie Li, Heng Huang, Xinbo Gao. Binarized Neural Network for Single Image Super Resolution. European Conference on Computer Vision (ECCV 2020), in press.

Alireza Ganjdanesh, Kamran Ghasedi, Liang Zhan, Weidong Cai, Heng Huang. Predicting Potential Propensity of Adolescents to Drugs via New Semi-Supervised Deep Ordinal Regression Model. Medical Image Computing and Computer Assisted Interventions (MICCAI 2020), in press.

Haozhe Jia, Shenzhen, Yong Xia, Weidong Cai, Heng Huang. Learning High-Resolution and Efficient Non-local Features for Brain Glioma Segmentation in MR Images. Medical Image Computing and Computer Assisted Interventions (MICCAI 2020), in press.

Tiange Xiang, Chaoyi Zhang, Dongnan Liu, Yang Song, Heng Huang, Weidong Cai. BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture. Medical Image Computing and Computer Assisted Interventions (MICCAI 2020), in press.

Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang. Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data. The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), pp. 2483-2493.

Junyi Li, Heng Huang. Faster Secure Data Mining via Distributed Homomorphic Encryption. The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), pp. 2706-2714.

Maosen Li, Cheng Deng, Tengjiao Li, Junchi Yan, Xinbo Gao, Heng Huang. Towards Transferable Targeted Attack. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020), pp. 638-646.

Shangqian Gao, Feihu Huang, Jian Pei, Heng Huang. Discrete Model Compression With Resource Constraint for Deep Neural Networks. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020), pp. 1896-1905.

An Xu, Zhouyuan Huo, Heng Huang. On the Acceleration of Deep Learning Model Parallelism With Staleness. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020), pp. 2085-2094.

Dongnan Liu, Donghao Zhang, Yang Song, Fan Zhang, Lauren O'Donnell, Heng Huang, Mei Chen, Weidong Cai. Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-Weighting. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020), pp. 4242-4251.

Zhiyuan Dang, Cheng Deng, Xu Yang, Heng Huang. Multi-Scale Fusion Subspace Clustering Using Similarity Constraint. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020), pp. 6657-6666.

Lei Luo, Jian Pei, Heng Huang. Sinkhorn Regression. the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI 2020), pp. 2598-2604.

Kamran Ghasedi, Wei Chen, Heng Huang. Deep Large-Scale Multi-Task Learning Network for Gene Expression Inference. The 24th International Conference on Research in Computational Molecular Biology (RECOMB 2020), pp. 19-36.

Zhou Zhai, Bin Gu, Xiang Li, Heng Huang. Safe Sample Screening for Robust Support Vector Machine. Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), pp. 6981-6988.

Wanli Shi, Bin Gu, Xiang Li, Heng Huang. Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization. Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), pp. 5734-5741.

Zhiyuan Dang, Xiang Li, Bin Gu, Cheng Deng, Heng Huang. Large-Scale Nonlinear AUC Maximization via Triply Stochastic Gradients. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), in press, 2020.

Bin Gu, Wenhan Xian, Zhouyuan Huo, Cheng Deng, Heng Huang. A Unified q-Memorization Framework for Asynchronous Stochastic Optimization. Journal of Machine Learning Research (JMLR), in press, 2020.

Dongnan Liu, Donghao Zhang, Yang Song, Fan Zhang, Lauren O'Donnell, Heng Huang, Mei Chen, Weidong Cai. PDAM: A Panoptic-level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images. IEEE Transactions on Medical Imaging (TMI), in press, 2020.

Bin Gu, Zhou Zhai, Cheng Deng, Heng Huang. Efficient Active Learning by Querying Discriminative and Representative Samples and Fully Exploiting Unlabeled Data. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), in press, 2020.

Bin Gu, Xiang Geng, Xiang Li, Wanli Shi, Guansheng Zheng, Cheng Deng, Heng Huang. Scalable Kernel Ordinal Regression via Doubly Stochastic Gradients. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), in press, 2020.

Xinjun Wang, Zhe Sun, Yanfu Zhang, Zhongli Xu, Hongyi Xin, Heng Huang, Richard Duerr, Kong Chen, Ying Ding, Wei Chen. BREM-SC: A Bayesian Random Effects Mixture Model for Joint Clustering Single Cell Multi-omics Data. Nucleic Acids Research, 48(11), pp. 58145824, 2020.

Qi Yan, Daniel E. Weeks, Hongyi Xin, Anand Swaroop, Emily Y. Chew, Heng Huang, Ying Ding, Wei Chen. Deep-learning-based Prediction of Late Age-Related Macular Degeneration Progression. Nature Machine Intelligence, 2(2):141-150, 2020.

Lodewijk Brand, Kai Nichols, HuaWang, Li Shen, Heng Huang. Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer's Disease Prediction. IEEE Transactions on Medical Imaging (TMI), 39(6): 1845-1855, 2020.

Yangli-ao Geng, Qingyong Li, Mingfei Liang, Chong-Yung Chi, Juan Tan, Heng Huang. Local-Density Subspace Distributed Clustering for High-Dimensional Data. IEEE Transactions on Parallel and Distributed Systems (TPDS), 31(8): 1799-1814, 2020.


Shuo Chen, Lei Luo, Jian Yang, Chen Gong, Jun Li, Heng Huang. Curvilinear Distance Metric Learning. Neural Information Processing Systems (NeurIPS 2019), pp. 4225-4234.

Qian Yang, Zhouyuan Huo, Wenlin Wang, Heng Huang, Larry Carin. Ouroboros: On Accelerating Training of Transformer-Based Language Models. Neural Information Processing Systems (NeurIPS 2019), pp. 5520-5530.

Runxue Bao, Bin Gu, Heng Huang. Efficient Approximate Solution Path Algorithm for Order Weight L1-Norm with Accuracy Guarantee. IEEE International Conference on Data Mining (ICDM 2019), pp. 958-963.

Yanfu Zhang, Liang Zhan, Weidong Cai, Paul Thompson, Heng Huang. Integrating Heterogeneous Brain Networks for Predicting Brain Disease Conditions. the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), pp. 214-222.

Lyujian Lu, Saad Elbeleidy, Lauren Baker, HuaWang, Li Shen, Heng Huang. Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions. the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), pp. 140-148.

Haozhe Jia, Yang Song, Heng Huang, Weidong Cai, Yong Xia. HD-Net: Hybrid Discriminative Network for Prostate Segmentation in MR Images. the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), pp. 110-118.

Igor Fortel, Mitchell Butler, Laura Korthauer, Liang Zhan, Yanfu Zhang, Lei Guo, Heng Huang, Ira Driscoll, Olusola Ajilore, Anastasios Sidiropoulos, Dan Schonfeld, Alex Leow . Brain Dynamics Through the Lens of Statistical Mechanics by Unifying Structure and Function. the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), pp. 503-511.

Feng Zheng, Cheng Deng, Heng Huang. Binarized Neural Networks for Resource-Ecient Hashing with Minimizing Quantization Loss. 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 1032-1040.

Bin Gu, Wenhan Xian, Heng Huang. Asynchronous Stochastic Frank-Wolfe Algorithms for Nonconvex Optimization. 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 737-743.

Wanli Shi, Xiang Geng, Xiang Li, Bin Gu, Heng Huang. Quadruply Stochastic Gradients for Large-Scale Nonlinear Semi-Supervised AUC Optimization. 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 3418-3424.

Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang. Scalable Semi-Supervised SVM via Triply Stochastic Gradients. 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 2364-2370.

Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang. Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 2549-2555.

Hongchang Gao, Jian Pei, Heng Huang. Conditional Random Field Enhanced Graph Convolutional Neural Networks. 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), pp. 276-284.

Hongchang Gao, Jian Pei, Heng Huang. ProGAN: Network Embedding via Proximity Generative Adversarial Network. 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), pp. 1308-1316.

Shuyang Yu, Bin Gu, Kunpeng Ning, Haiyan Chen, Jian Pei, Heng Huang. Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning. 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), pp. 1587-1595.

Chenyou Fan, Yuze Zhang, Yi Pan, Xiaoyue Li, Chi Zhang, Rong Yuan, Di Wu, Wensheng Wang, Jian Pei, Heng Huang. Multi-Horizon Time Series Forecasting with Temporal Attention Learning. 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), pp. 2527-2535.

Feihu Huang, Songcan Chen, Heng Huang. Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization. The 36th International Conference on Machine Learning (ICML 2019), pp. 2839-2848.

Hongchang Gao, Jian Pei, Heng Huang. Demystifying Dropout. The 36th International Conference on Machine Learning (ICML 2019), pp. 2112-2121.

Yanfu Zhang, Heng Huang. Brain Connectome Based Complex Brain Disorder Prediction via Novel Graph-Blind Convolutional Network. The 26th International Conference on Information Processing in Medical Imaging (IPMI 2019), pp. 669-681.

Shangqian Gao, Cheng Deng, Heng Huang. Cross Domain Model Compression by Structured Weight Sharing. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019), pp. 8973-8982.

Kamran Ghasedi, Cheng Deng, Heng Huang. Balanced Self-Paced Learning for Generative Adversarial Clustering Network. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019), pp. 4391-4400.

Chengyou Fang, Xiaofan Zhang, Shu Zhang, Wensheng Wang, Chi Zhang, Heng Huang. Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019), pp. 1999-2007.

Bin Gu, Zhouyuan Huo, Heng Huang. Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), pp. 3697-3704.

Lei Luo, Jie Xu, Cheng Deng, Heng Huang. Orthogonality-Promoting Dictionary Learning via Bayesian Inference. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), pp. 4472-4479.

Lei Luo, Jie Xu, Cheng Deng, Heng Huang. Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), pp. 4480-4487.

Feihu Huang, Bing Gu, Zhouyuan Huo, Songcan Chen, Heng Huang. Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), pp. 1503-1510.

Haozhe Jia, Yong Xia, Yang Song, Donghao Zhang, Heng Huang, Yanning Zhang, Weidong Cai. 3D APA-Net: 3D Adversarial Pyramid Anisotropic Convolutional Network for Prostate Segmentation in MR Images. IEEE Transactions on Medical Imaging (TMI), 39(2): 447-457, 2019.

Kamran Ghasedi, Hongchong Gao, Yanhua Yang, Heng Huang, Cheng Deng. Robust Cumulative Crowdsourcing Framework Using New Incentive Payment Function and Joint Aggregation Model. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), in press, 2019.

Jiexi Yan, Cheng Deng, Lei Luo, Xiaoqian Wang, Xiaohui Yao, Li Shen, Heng Huang. Identifying Imaging Markers for Predicting Cognitive Assessments Using Wasserstein Distances Based Matrix Regression. Frontiers Neuroscience, 13: 668, 2019.

Zhe Guo, Xiang Li, Heng Huang, Ning Guo, Quanzheng Li. Deep Learning-based Image Segmentation on Multi-modal Medical Imaging. IEEE Transactions on Radiation and Plasma Medical Sciences, pp. 162-169, 2019.

Shuai Zheng, Chris Ding, Feiping Nie, Heng Huang. Harmonic Mean Linear Discriminant Analysis. IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(8): 1520-1531, 2019.

Lei Luo, Jian Yang, Yigong Zhang, Yong Xu, Heng Huang. Nesting-structured Nuclear Norm Minimization for Spatially Correlated Matrix Variate. Pattern Recognition, 91: 147-161, 2019.

Zhou Chen, Mingwu Jin, Yue Deng, Jing-SongWang, Heng Huang, Xiaohua Deng, Chun-Ming Huang. Improvement of a Deep Learning Algorithm for Total Electron Content Maps: Image Completion. Journal of Geophysical Research Space Physics, 124(1), 790-800, 2019.


Zhouyuan Huo, Bin Gu, Heng Huang. Training Neural Networks Using Features Replay. Neural Information Processing Systems (NeurIPS 2018), in press.

Jie Xu, Lei Luo, Cheng Deng, Heng Huang. Bilevel Distance Metric Learning for Robust Image Recognition. Neural Information Processing Systems (NeurIPS 2018), in press.

Zhouyuan Huo, Heng Huang. Asynchronous Dual Free Stochastic Dual Coordinate Ascent for Distributed Data Mining. IEEE International Conference on Data Mining (ICDM 2018), in press.

Xiaoqian Wang, Kamran Ghasedi and Heng Huang. Conditional Generative Adversarial Network for Gene Expression Inference. 17th European Conference on Computational Biology (ECCB 2018), in Bioinformatics, 34(17), pp. i603-i611.

Xiaoqian Wang, Hong Chen, Jingwen Yan, Kwangsik Nho, Shannon Risacher, Andrew Saykin, Li Shen and Heng Huang. Quantitative Trait Loci Identification for Brain Endophenotypes via New Additive Model with Random Networks. 17th European Conference on Computational Biology (ECCB 2018), in Bioinformatics, 34(17), pp. i866-i874.

Xiaoqian Wang, Weidong Cai, Dinggang Shen, Heng Huang. Temporal Correlation Structure Learning for MCI Conversion Prediction. 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018), in press.

Donghao Zhang, Yang Song, Dongnan Liu, Haozhe Jia, Siqi Liu, Yong Xia, Heng Huang, Weidong Cai. Panoptic Segmentation with an End-to-end Cell R-CNN for Pathology Image Analysis. 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018), in press.

Lodewijk Brand, Hua Wang, Heng Huang, Shannon Risacher, Andrew Saykin, Li Shen. Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease. 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018), in press.

Jie Xu, Lei Luo, Cheng Deng, Heng Huang. New Robust Metric Learning Model Using Maximum Correntropy Criterion. 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), pp. 2555-2564.

Bin Gu, Xiao-Tong Yuan, Songcan Chen, Heng Huang. New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine. 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), pp. 1475-1484.

Hongchang Gao, Heng Huang. Self-Paced Network Embedding. 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), pp. 1406-1415.

Kamran Ghasedi, Xiaoqian Wang, Heng Huang. Semi-Supervised Generative Adversarial Network for Gene Expression Inference. 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), pp. 1435-1444.

Zhouyuan Huo, Bin Gu, Heng Huang. Decoupled Parallel Backpropagation with Convergence Guarantee. The 35th International Conference on Machine Learning (ICML 2018), pp. 1807-1816.

Bin Gu, Zhouyuan Huo, Heng Huang. Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines. The 35th International Conference on Machine Learning (ICML 2018), pp. 2103-2111.

Hongchang Gao, Heng Huang. Deep Attributed Network Embedding. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 3364-3370.

Hongchang Gao, Heng Huang. Joint Generative Moment-Matching Network for Learning Structural Latent Code. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 2121-2127.

Hongchang Gao, Heng Huang. Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 2128-2134.

Feng Zheng, Xin Miao, Heng Huang. Fast Vehicle Identification in Surveillance via Ranked Semantic Sampling Based Embedding. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 3697-3703.

Jie Xu, Lei Luo, Heng Huang. Multi-Level Metric Learning via Smoothed Wasserstein Distance. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 2919-2925.

Xiaoqian Wang, Yijun Huang, Ji Liu, Heng Huang. New Balanced Active Learning Model and Optimization Algorithm. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 2826-2832.

Xin Miao, Xiantong Zhen, Vassilis Athitsos, Xianglong Liu, Cheng Deng, Heng Huang. Direct Shape Regression Networks for End-to-End Face Alignment. The Thirtieth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018), in press.

Kamran Ghasedi Dizaji, Feng Zheng, Najmeh Sadoughi Nourabadi, Yanhua Yang, Cheng Deng, Heng Huang. Unsupervised Deep Generative Adversarial Hashing Network. The Thirtieth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018), in press.

Bin Gu, Zhouyuan Huo, Heng Huang. Asynchronous Doubly Stochastic Group Regularized Learning. The 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), pp. 1791-1800.

Bin Gu, Xin Miao, Zhouyuan Huo, Heng Huang. Asynchronous Doubly Stochastic Sparse Kernel Learning. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 3085-3092.

Zhouyuan Huo, Bin Gu, Ji Liu, Heng Huang. Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 3287-3294.

Lei Luo, Heng Huang. Matrix Variate Gaussian Mixture Distribution Steered Robust Metric Learning. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 3722-3729.

Bin Gu, De Wang, Zhouyuan Huo, Heng Huang. Inexact Proximal Gradient Methods for Non-Convex and Non-Smooth Optimization. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 3093-3100.

Kamran Ghasedi, Heng Huang. Sentiment Analysis via Deep Hybrid Textual-Crowd Learning Model. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 1563-1570.

Feng Zheng, Heng Huang. Direct Hashing without Pseudo-Labels. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 4539-4546.

Zhouyuan Huo, Dinggang Shen, Heng Huang. Genotype-phenotype association study via new multi-task learning model. Twenty-Third Pacific Symposium on Biocomputing (PSB 2018), pp. 353-364.

Kamran Ghasedi, Yanhua Yang, Heng Huang. Joint Generative-Discriminative Aggregation Model for Multi-Option Crowd Labels. The 11th ACM International Conference on Web Search and Data Mining (WSDM 2018), pp. 144-152.

Xiaoqian Wang, Xiantong Zhen, Quanzheng Li, Dinggang Shen, Huang, Heng. Cognitive Assessment Prediction in Alzheimers Disease by Multi-Layer Multi-Target Regression. Neuroinformatics, 16(3-4), pp. 285-294, 2018.

Afaf Tareef, Yang Song, Heng Huang, Dagan Feng, Mei Chen, Yue Wang, Weidong Cai. Multipass Fast Watershed for Accurate Segmentation of Overlapping Cervical Cells. IEEE Transactions on Medical Imaging (TMI), 37(9), pp. 2044-2059, 2018.

Nha Nguyen, An Vo, Haibin Sun, Heng Huang. Heavy-Tailed Noise Suppression and Derivative Wavelet Scalogram for Detecting DNA Copy Number Aberrations. IEEE/ACM Transactions Computational Biology and Bioinformatics (TCBB), 15(5): 1625-1635, 2018.

Wenhao Jiang, Hongchang Gao, Wei Lu, Wei Liu, Fu-lai Chung, Huang, Heng. Stacked Robust Adaptively Regularized Auto-regressions for Domain Adaptation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(3), pp. 561-574, 2018.

Lei Luo, Jian Yang, Bob Zhang, Jielin Jiang, Heng Huang. Nonparametric Bayesian Correlated Group Regression with Applications to Image Classification. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), in press, 2018.


Hong Chen, Xiaoqian Wang, Cheng Deng, Heng Huang. Group Sparse Additive Machine. Neural Information Processing Systems (NIPS 2017), pp. 197-207.

Xiaoqian Wang, Hong Chen, Weidong Cai, Dinggang Shen, Heng Huang. Regularized Modal Regression with Applications in Cognitive Impairment Prediction. Neural Information Processing Systems (NIPS 2017), pp. 1447-1457.

Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang. Learning A Structured Optimal Bipartite Graph for Co-Clustering. Neural Information Processing Systems (NIPS 2017), pp. 4132-4141.

Kamran Ghasedi, Amirhossein Herandi, Cheng Deng, Weidong Cai, Heng Huang. Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization. International Conference on Computer Vision (ICCV 2017), pp. 5747-5756.

Yang Song, Fan Zhang, Qing Li, Heng Huang, Lauren J. O'Donnel,Weidong Cai. Locally-Transferred Fisher Vectors for Texture Classification. International Conference on Computer Vision (ICCV 2017), pp. 4922-4930.

Bin Gu, Guodong Liu, Heng Huang. Groups-Keeping Solution Path Algorithm for Sparse Regression with Automatic Feature Grouping. 23nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017), pp. 185-193.

Yang Song, Hang Chang, Heng Huang, Weidong Cai. Supervised Intra-Embedding of Fisher Vectors for Histopathology Image Classification. 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2017), pp. 99-106.

Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang. Predicting Interrelated Alzheimer's Disease Outcomes via New Self-Learned Structured Low-Rank Model. The 25th Biennial International Conference on Information Processing in Medical Imaging (IPMI 2017), pp. 198-209.

Feiping Nie, Zhouyuan Huo, Heng Huang. Joint Capped Norms Minimization for Robust Matrix Recovery. The 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 2557-2563.

Wenhao Jiang, Cheng Deng, Wei Liu, Feiping Nie, Fu Korris, Heng Huang. Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning. The 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 1958-1964.

Jie Xu, Cheng Deng, Xinbo Gao, Dinggang Shen, Heng Huang. Predicting Alzheimer's Disease Cognitive Assessment via Robust Low-Rank Structured Sparse Model. The 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 3880-3886.

Jie Xu, Xianglong Liu, Zhouyuan Huo,Cheng Deng, Feiping Nie, Heng Huang. Maximizing Multi-Class Margins for Supervised and Semi-Supervised Support Vector Machine. The 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 3154-3160.

Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang. Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-Learning Predictive Model. The 21st Annual International Conference on Research in Computational Molecular Biology (RECOMB 2017), pp. 287-302.

Zhouyuan Huo, Heng Huang. Asynchronous Mini-Batch Gradient Descent with Variance Reduction for Non-Convex Optimization. Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), pp. 2043-2049.

Hongchang Gao, Feiping Nie, Heng Huang. Local Centroids Structured Non-negative Matrix Factorization. Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), pp. 1905-1911.

Feiping Nie, Xiaoqian Wang, Heng Huang. Multiclass Capped lp-Norm SVM for Robust Classifications. Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), pp. 2415-2421.

Zhouyuan Huo, Shangqian Gao,Weidong Cai, Heng Huang. Video Recovery via Learning Variation and Consistency of Images. Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), pp. 4082-4088.

Yun Liu, Yiming Guo, Hua Wang, Feiping Nie, Heng Huang. Semi-Supervised Classifications via Elastic and Robust Embedding. Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), pp. 2294-2300.

Afaf Tareef, Yang Song, Weidong Cai, Heng Huang, Hang Chang, Yue Wang, Michael J. Fulham, Dagan Feng, Mei Chen. Automatic segmentation of overlapping cervical smear cells based on local distinctive features and guided shape deformation. Neurocomputing 221: 94-107, 2017.

Afaf Tareef, Yang Song, Heng Huang, Yue Wang, Dagan Feng, Mei Chen, Weidong Cai. Optimizing the cervix cytological examination based on deep learning and dynamic shape modeling. Neurocomputing, 248: 28-40, 2017.

Yang Song, Qing Li, Fan Zhang, Heng Huang, Dagan Feng, Yue Wang, Mei Chen, Weidong Cai. Dual discriminative local coding for tissue aging analysis. Medical Image Analysis, 38: 65-76, 2017.

Yan-shuo Chang, Feiping Nie, Zhihui Li, Xiaojun Chang, Heng Huang. Refined Spectral Clustering via Embedded Label Propagation. Neural Computation, 29(12), 2017.

Xiaofeng Zhu, Heung-Il Suk, Heng Huang, Dinggang Shen. Low-Rank Graph-Regularized Structured Sparse Regression for Identifying Genetic Biomarkers. IEEE Transactions on Big Data 3(4): 405-414, 2017.

Hua Wang, Lin Yan, Heng Huang, Chris Ding. From Protein Sequence to Protein Function via Multi-Label Linear Discriminant Analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB). 14(3): 503-513, 2017.

Yang Song, Qing Li, Heng Huang, Dagan Feng, Mei Chen, Weidong Cai. Low Dimensional Representation of Fisher Vectors for Microscopy Image Classification. IEEE Transactions on Medical Imaging, 36(8): 1636-1649, 2017.


Hong Chen, Haifeng Xia, Weidong Cai, Heng Huang. Error Analysis of Generalized Nystrom Kernel Regression. Neural Information Processing Systems (NIPS 2016), pp. 2541-2549.

Hongchang Gao, Xiaoqian Wang, Heng Huang. New Robust Clustering Model for Identifying Cancer Genome Landscapes. IEEE International Conference on Data Mining (ICDM 2016), pp. 151-160.

Dijun Luo, Zhouyuan Huo, YangWang, Andrew J. Saykin, Li Shen, Heng Huang. New Probabilistic Multi-Graph Decomposition Model to Identify Consistent Human Brain Network Modules. IEEE International Conference on Data Mining (ICDM 2016), pp. 301-310.

De Wang, Feiping Nie, Heng Huang. Learning Task Relational Structure for Multi-Task Feature Learning. IEEE International Conference on Data Mining (ICDM 2016), pp. 1239-1244.

Xiaoqian Wang, Feiping Nie, Heng Huang. Structured Doubly Stochastic Matrix for Graph Based Clustering. 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), Research Track, pp. 1245-1254.

Zhouyuan Huo, Feiping Nie, Heng Huang. Robust and Effective Metric Learning Using Capped Trace Norm. 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), Research Track, pp. 1605-1614.

Zhouyuan Huo, Dinggang Shen, Heng Huang. New Multi-Task Learning Model to Predict Alzheimer's Disease Cognitive Assessment. 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2016), pp. 317-325.

Xiaoqian Wang, Dinggang Shen, Heng Huang. Prediction of Memory Impairment with MRI Data: A Longitudinal Study of Alzheimer's Disease. 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2016), pp. 273-281.

Xiaofeng Zhu, Heung-Il Suk, Heng Huang, Dinggang Shen. Structured Spare Low-Rank Regression Model for Brain-Wide and Genome-Wide Associations. 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2016), pp. 344-352.

De Wang, Feiping Nie, Heng Huang. Fast Robust Non-negative Matrix Factorization for Large-Scale Data Clustering. 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 2104-2110.

Feiping Nie, Heng Huang. Subspace Clustering via New Discrete Group Structure Constrained Low-Rank Model. 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 1874-1880.

Feiping Nie, Xiaoqian Wang, Michael I. Jordan, Heng Huang. The Constrained Laplacian Rank Algorithm for Graph-Based Clustering. Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016), pp. 1969-1976.

Zhouyuan Huo, Ji Liu, Heng Huang. Optimal Discrete Matrix Completion. Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016), pp. 424-430.

Wenhao Jiang, Hongchang Gao, Fu-Lai Korris Chung, Heng Huang. The l2,1-Norm Stacked Robust Autoencoders for Domain Adaptation. Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016), pp. 1723-1729.

Hua Wang, Cheng Deng, Hao Zhang, Xinbo Gao, Heng Huang. Learning Biological Relevance of Drosophila Embryos for Drosophila Gene Expression Pattern Annotations. Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016), pp. 1324-1330.

Feiping Nie, Hua Wang, Cheng Deng, Xinbo Gao, Xuelong Li, Heng Huang. New l1-Norm Relaxations and Optimizations for Graph Clustering. Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016), pp. 1962-1968.

Yang Song, Weidong Cai, Heng Huang, Dagan Feng, Yue Wang, Mei Chen. Bioimage classification with subcategory discriminant transform of high dimensional visual descriptors. BMC Bioinformatics 17: 465:1-465:15, 2016.

Lei Du, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen. Structured sparse CCA for brain imaging genetics via graph OSCAR. BMC Systems Biology 10(S-3): 68, 2016.

Xiaojun Chang, Feiping Nie, Yi Yang, Chengqi Zhang, Heng Huang. Convex Sparse PCA for Unsupervised Feature Learning. ACM Transactions on Knowledge Discovery from Data (TKDD), 11(1): 3:1-3:16, 2016.

Lei Du, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen, ADNI. Structured Sparse Canonical Correlation Analysis for Brain Imaging Genetics: An Improved GraphNet Method. Bioinformatics, 32(10):1544-51, 2016.


Hongchang Gao, Feiping Nie, Heng Huang. Multi-Modal Subspace Clustering. International Conference on Computer Vision (ICCV 2015), pp. 4238-4246.

Hongchang Gao, Feiping Nie, Weidong Cai, Heng Huang. Robust Capped Norm Nonnegative Matrix Factorization. 24th ACM International Conference on Information and Knowledge Management (CIKM 2015), pp. 871-880.

Peng Li, Weidong Cai, Heng Huang. Weakly Supervised Natural Language Processing Framework for Abstractive Multi-Document Summarization. 24th ACM International Conference on Information and Knowledge Management (CIKM 2015), pp. 1401-1410.

Hongchang Gao, Lin Yan, Weidong Cai, Heng Huang. Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors Integration. 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Conference (KDD 2015), pp. 339-348.

Hongchang Gao, Chengtao Cai, Jingwen Yan, Lin Yan, Joaquin Goni Cortes, Yang Wang, Feiping Nie, John West, Andrew Saykin, Li Shen, Heng Huang. Identifying Connectome Module Patterns via New Balanced Multi-Graph Normalized Cut. 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2015), pp. 169-176.

Xiaoqian Wang, Yun Liu, Feiping Nie, Heng Huang. Discriminative Unsupervised Dimensionality Reduction. Twenty-Fourth International Joint Conferences on Artificial Intelligence (IJCAI 2015), pp. 3925-3931.

Wenhao Jiang, Feiping Nie, Heng Huang. Robust Dictionary Learning with Capped L1 Norm. Twenty-Fourth International Joint Conferences on Artificial Intelligence (IJCAI 2015), pp. 3590-3596.

Jin Huang, Feiping Nie, Heng Huang. A New Simplex Sparse Learning Model to Measure Data Similarity for Clustering. Twenty-Fourth International Joint Conferences on Artificial Intelligence (IJCAI 2015), pp. 3569-3575.

Yang Song, Weidong Cai, Qing Li, Dagan Feng, Heng Huang. Fusing Subcategory Probabilities for Texture Classification. Twenty-Eighth IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015), pp. 4409-4417.

Hua Wang, Feiping Nie, Heng Huang. Learning Robust Locality Preserving Projection via p-Order Minimization. Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 3059-3065.

Yeqing Li, Feiping Nie, Heng Huang, Junzhou Huang. Large-Scale Multi-View Spectral Clustering via Bipartite Graph. Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 2750-2756.

Shuai Zheng, Xiao Cai, Chris Ding, Feiping Nie, Heng Huang. A Closed Form Solution to Multiview Low-rank Regression. Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 1973-1979.

De Wang, Feiping Nie, Heng Huang. Global Redundancy Minimization for Feature Ranking. IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(10), pp. 2743-2755, 2015.

Yang Song, Weidong Cai, Heng Huang, Yun Zhou, Yue Wang, David Dagan Feng. Locality constrained Subcluster Representation Ensemble for Lung Image Classification. Medical Image Analysis (MIA), 22(1), pp. 102-113, 2015.

Hua Wang, Feiping Nie, Heng Huang. Large-Scale Cross-Language Web Page Classification via Dual Knowledge Transfer Using Fast Nonnegative Matrix Tri-Factorization. ACM Transactions on Knowledge Discovery from Data (TKDD), 10(1), pp. 1:1-1:29, 2015.

Yang Song, Weidong Cai, Heng Huang, Yun Zhou, David Dagan Feng, Yue Wang, Michael J. Fulham, Mei Chen. Large Margin Local Estimate with Applications to Medical Image Classification. IEEE Transactions on Medical Imaging (TMI), 34(6), pp. 1362-1377, 2015.

Hua Wang, Heng Huang, Chris Ding. Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency. Journal of Computational Biology (JCB), 22(6), pp. 546-562, 2015.

Jinglei Lv, Xi Jiang, Xiang Li, Dajiang Zhu, Hanbo Chen, Tuo Zhang, Shu Zhang, Xintao Hu, Junwei Han, Heng Huang, Jing Zhang, Lei Guo, Tianming Liu. Sparse Representation of Whole-brain FMRI Signals for Identification of Functional Networks. Medical Image Analysis (MIA), 20(1), pp. 112-134, 2015.

Feiping Nie, Hua Wang, Heng Huang, Chris Ding. Joint Schatten p-Norm and lp-Norm Robust Matrix Completion for Missing Value Recovery. Knowledge and Information Systems (KAIS), 42(3), pp. 525-544, 2015.

Jingwen Yan, Taiyong Li, Hua Wang, Heng Huang, Jing Wan, Kwangsik Nho, Sungeun Kim, Shannon L. Risacher, Andrew J. Saykin, Li Shen. Cortical Surface Biomarkers for Predicting Cognitive Outcomes Using Group l2,1 Norm. Neurobiology of Aging, 36(1), pp. S185-S193, 2015.


Feiping Nie, Xiao Cai, Heng Huang. Flexible Shift-Invariant Locality and Globality Preserving Projections. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), Lecture Notes in Computer Science Volume 8725, pp. 485-500.

De Wang, Feiping Nie, Heng Huang. Unsupervised Feature Selection via Unified Trace Ratio Formulation and K-means Clustering (TRACK). European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), Lecture Notes in Computer Science Volume 8726, pp. 306-321.

De Wang, Yang Wang, Feiping Nie, Jingwen Yan, Weidong Cai, Andrew Saykin, Li Shen, Heng Huang. Human Connectome Module Pattern Detection Using A New Multi-Graph MinMax Cut Model. The 17th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2014), Lecture Notes in Computer Science Volume 8675, pp. 313-320.

Lei Du, Jingwen Yan, Sungeun Kim, Shannon Risacher, Heng Huang, Mark Inlow, Jason Moore, Andrew Saykin, Li Shen. A Novel Structure-Aware Sparse Learning Algorithm for Brain Imaging Genetics. The 17th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2014), Lecture Notes in Computer Science Volume 8675, pp. 329-336.

Yang Song, Weidong Cai, Heng Huang, Yun Zhou, Dagan Feng, Mei Chen. Large Margin Aggregation of Local Estimates for Medical Image Classification. The 17th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2014), Lecture Notes in Computer Science Volume 8674, pp. 196-203.

De Wang, Feiping Nie, Heng Huang. Large-Scale Adaptive Semi-Supervised Learning via Unified Inductive and Transductive Model. The 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2014), pp. 482-491.

Feiping Nie, Xiaoqian Wang, Heng Huang. Clustering and Projected Clustering via Adaptive Neighbor Assignment. The 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2014), pp. 977-986.

Feiping Nie, Jianjun Yuan, Heng Huang. Optimal Mean Robust Principal Component Analysis. The 31st International Conference on Machine Learning (ICML 2014), Journal of Machine Learning Research, W&CP, Vol. 32, No. 1, pp. 1062-1070.

Hua Wang, Feiping Nie, Heng Huang. Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization. The 31st International Conference on Machine Learning (ICML 2014), Journal of Machine Learning Research, W&CP, Vol. 32, No. 1, pp. 1836-1844.

Feiping Nie, Yizhen Huang, Heng Huang. New Primal SVM Solver with Linear Computational Cost for Big Data Classifications. The 31st International Conference on Machine Learning (ICML 2014), Journal of Machine Learning Research, W&CP, Vol. 32, No. 1, pp. 505-513.

Hua Wang, Feiping Nie, Heng Huang. Video Recovery via Low-Rank Tensor Completion with Spatio-Temporal Consistency. Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2014), pp. 2846-2852.

Hua Wang, Feiping Nie, Heng Huang. Globally and Locally Consistent Unsupervised Projection. Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2014), pp. 1328-1333.

Xiaojun Chang, Feiping Nie, Yi Yang, Heng Huang. A Convex Formulation for Semi-Supervised Multi-Label Feature Selection. Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2014), pp. 1171-1177.

Dijun Luo, Heng Huang. Video Motion Segmentation Using New Adaptive Manifold Denoising Model. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), pp. 65-72.

Hua Wang, Heng Huang, Chris Ding. Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency. The 18th International Conference on Research in Computational Molecular Biology (RECOMB 2014), pp. 311-325.

Franklin Quilumba, Wei-jen Lee, Heng Huang, David Wang, Robert Szabados. Using Smart Meter Data to Improve the Accuracy of Intra-Day Load Forecasting Considering Customer Behavior Similarities. IEEE Transactions on Smart Grid, 6(2), pp. 911-918, 2014.

Ziming Zhang, Heng Huang, Dinggang Shen. Integrative Analysis of Multi-Dimensional Imaging Genomics Data for Alzheimer's Disease Prediction. Frontiers in Aging Neuroscience, 6: 260, 2014.

Jingwen Yan, Lei Du, Sungeun Kim, Shannon L. Risacher, Heng Huang, Jason H. Moore, Andrew J. Saykin, Li Shen. Transcriptome-Guided Amyloid Imaging Genetic Analysis via A Novel Structured Sparse Learning Algorithm. Bioinformatics, 30(17), pp. i564-i571, 2014.

Fan Zhang, Yang Song, Weidong Cai, Min-Zhao Lee, Yun Zhou, Heng Huang, Shimin Shan, Michael J Fulham, Dagan Feng. Lung Nodule Classification with Multi-Level Patch-Based Context Analysis, IEEE Transactions on Biomedical Engineering, 61(4), pp. 1155-1166, 2014.

Guorong Wu, Qian Wang, Daoqiang Zhang, Feiping Nie, Heng Huang, Dinggang Shen. A Generative Probability Model of Joint Label Fusion for Multi-Atlas Based Brain Segmentation, Medical Image Analysis, 18(6), pp. 881-890, 2014.

Vangelis Metsis, Fillia Makedon, Dinggang Shen, Heng Huang. DNA Copy Number Selection Using Robust Structured Sparsity-Inducing Norms, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(1), pp. 168-181, 2014.

Yang Song, Weidong Cai, Heng Huang, Xiaogang Wang, Yun Zhou, Michael J Fulham, David Dagan Feng. Lesion Detection and Characterization with Context Driven Approximation in Thoracic FDG PET-CT Images of NSCLC Studies, IEEE Transactions on Medical Imaging (TMI) , 33(2), pp. 408-421, 2014.


Hua Wang, Feiping Nie, Weidong Cai, Heng Huang. Semi-Supervised Robust Dictionary Learning via Efficient l2,0+-Norms Minimization. International Conference on Computer Vision (ICCV 2013), pp. 1145-1152.

Xiao Cai, Feiping Nie, Weidong Cai, Heng Huang. New Graph Structured Sparsity Model for Multi-Label Image Annotations. International Conference on Computer Vision (ICCV 2013), pp. 801-808.

Xiao Cai, Feiping Nie, Weidong Cai, Heng Huang. Heterogeneous Image Features Integration via Multi-Modal Semi-Supervised Learning Model. International Conference on Computer Vision (ICCV 2013), pp. 1737-1744.

Heng Huang, Jingwen Yan, Feiping Nie, Jin Huang, Weidong Cai, Andrew J. Saykin, Li Shen. A New Sparse Learning Model for Brain Anatomical and Genetic Network Analysis. The 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2013), pp. 625-632.

Yang Song, Weidong Cai, Heng Huang, Xiaogang Wang, Stefan Eberl, Michael Fulham, Dagan Feng. Similarity Guided Feature Labeling for Lesion Detection. The 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2013), pp. 284-291.

Xiao Cai, Chris Ding, Feiping Nie, Heng Huang. On The Equivalent of Low-Rank Linear Regressions and Linear Discriminant Analysis Based Regressions. The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2013), pp. 1124-1132.

Hua Wang, Feiping Nie, Heng Huang. Robust and Discriminative Self-Taught Learning. The 30th International Conference on Machine Learning (ICML 2013), Journal of Machine Learning Research, W&CP, Vol. 28, No. 3, pp. 298-306.

Hua Wang, Feiping Nie, Heng Huang. Multi-View Clustering and Feature Learning via Structured Sparsity. The 30th International Conference on Machine Learning (ICML 2013), Journal of Machine Learning Research, W&CP, Vol. 28, No. 3, pp. 352-360.

Feiping Nie, Hua Wang, Heng Huang, Chris Ding. Early Active Learning via Robust Representation and Structured Sparsity. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), pp. 1572-1578.

Feiping Nie, Hua Wang, Heng Huang, Chris Ding. Adaptive Loss Minimization for Semi-Supervised Elastic Embedding. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), pp. 1565-1571.

Hua Wang, Heng Huang, Chris Ding. Protein Function Prediction via Laplacian Network Partitioning Incorporating Function Category Correlations. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), pp. 2049-2056.

Xiao Cai, Feiping Nie, Heng Huang. Exact Top-k Feature Selection via l2,0-Norm Constraint. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), pp. 1240-1246.

Xiao Cai, Feiping Nie, Heng Huang. Multi-View K-Means Clustering on Big Data. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), pp. 2598-2604.

Jin Huang, Feiping Nie, Heng Huang, Yu Lei, Chris Ding. Social Trust Prediction Using Rank-k Matrix Recovery. 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), pp. 2647-2653.

Jin Huang, Feiping Nie, Heng Huang, Chris Ding. Supervised and Projected Sparse Coding for Image Classification. Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13 main track), pp. 438-444.

Jin Huang, Feiping Nie, Heng Huang. Robust Discrete Matrix Completion. Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13 main track), pp. 424-430.

Jin Huang, Feiping Nie, Heng Huang. Spectral Rotation vs K-means in Spectral Clustering. Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13 main track), pp. 431-437.

Hua Wang, Feiping Nie, Heng Huang. Heterogeneous Visual Features Fusion via Sparse Multimodal Machine. 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2013), pp. 3095-3100.

De Wang, Feiping Nie, Heng Huang, Jingwen Yan, Shannon Risacher, Andrew Saykin, Li Shen. Structural Brain Network Constrained Neuroimaging Marker Identification for Predicting Cognitive Functions. International Conference on Information Processing in Medical Imaging (IPMI 2013), pp. 536-547.

Yang Song, Weidong Cai, Heng Huang, Yue Wang, David Dagan Feng, Mei Chen. Region-based progressive localization of cell nuclei in microscopic images with data adaptive modeling, BMC Bioinformatics , Vol. 14, No. 173, 2013.

Jin Huang, Feiping Nie, Heng Huang, Yicheng Tu, Yu Lei. Social Trust Prediction Using Heterogeneous Networks, ACM Transactions on Knowledge Discovery from Data (TKDD), 7(4), pp. 17:1-17:21, 2013.

Dijun Luo, Chris Ding, Heng Huang. Towards Structural Sparsity: An Explicit l2/l0 Approach. Knowledge and Information Systems, Vol. 36, pp. 411-443, 2013.

Jin Huang, Feiping Nie, Heng Huang, Chris Ding. Robust Manifold Non-Negative Matrix Factorization. ACM Transactions on Knowledge Discovery from Data (TKDD), 8(3), pp. 11:1-11:21, 2013.

Hua Wang, Heng Huang, Chris Ding. Function-Function Correlated Multi-Label Protein Function Prediction over Interaction Networks. Journal of Computational Biology (JCB), Vol. 20, No. 4, pp. 322-343, 2013.

Hua Wang, Heng Huang, Chris Ding, Feiping Nie. Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization. Journal of Computational Biology (JCB), Vol. 20, No. 4, pp. 344-358, 2013.

Hua Wang, Heng Huang, Fillia Makedon. Emotion Detection via Discriminant Laplacian Embedding. International Journal Universal Access in the Information Society, Springer, pp. 1-9, 2013.


Feiping Nie, Hua Wang, Heng Huang, Chris Ding. Robust Matrix Completion via Joint Schatten p-Norm and lp-Norm Minimization. ICDM 2012, pp. 566-574 (acceptance rate for full paper 81/756=10.7%).

Dijun Luo, Chris Ding, Heng Huang. Parallelization with Multiplicative Algorithms for Big Data Mining. ICDM 2012, pp. 489-498 (acceptance rate for full paper 81/756=10.7%).

Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon Risacher, Andrew Saykin, Li Shen. High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer Disease Progression Prediction. NIPS 2012, pp. 1286-1294 (acceptance rate for oral paper 20/1467=1.36%).

Dijun Luo, Chris Ding, Heng Huang. Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach. NIPS 2012, pp. 2969-2977.

Jin Huang, Feiping Nie, Heng Huang, Yi-Cheng Tu. Trust Prediction via Aggregating Heterogeneous Social Networks. ACM Conference on Information and Knowledge Management (CIKM 2012), pp. 1774-1778.

Xiao Cai, Hua Wang, Heng Huang, Chris Ding. Joint Image Classification and Annotation via Biased Random Walk on Tri-Relational Graph. European Conference on Computer Vision (ECCV 2012), pp. 823-836.

Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen. From Phenotype to Genotype: An Association Study of Candidate Phenotypic Markers to Alzheimer's Disease Relevant SNPs. European Conference on Computational Biology (ECCB 2012) , (acceptance rate 14%, 48/341), Bioinformatics, Vol. 28, No. 18, pp. i619-i625, 2012.

Hanbo Chen, Xiao Cai, Dajiang Zhu, Feiping Nie, Tianming Liu, Heng Huang. Group-wise Consistent Parcellation of Gyri via Adaptive Multi-View Spectral Clustering of Fiber Shapes. The 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2012) , pp. 271-279.

Deguang Kong, Chris Ding, Heng Huang, Feiping Nie. An Iterative Locally Linear Embedding Algorithm. The 29th International Conference on Machine Learning (ICML 2012), pp. 1647-1654.

Xiao Cai, Hua Wang, Heng Huang, Chris Ding. Joint Stage Recognition and Anatomical Annotation of Drosophila Gene Expression Patterns. 20th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2012), published in Bioinformatics, (acceptance rate for proceeding paper 13.4%, 36/268), Bioinformatics, Vol. 28, No. 12, pp. i16-i24, 2012.

Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen, ADNI. Identifying Disease Sensitive and Quantitative Trait Relevant Biomarkers from Multi-Dimensional Heterogeneous Imaging Genetics Data via Sparse Multi-Modal Multi-Task Learning. 20th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2012), published in Bioinformatics, (acceptance rate for proceeding paper 13.4%, 36/268), Bioinformatics, Vol. 28, No. 12, pp. i127-i136, 2012.

Feiping Nie, Heng Huang, Chris Ding. Low-Rank Matrix Recovery via Efficient Schatten p-Norm Minimization, Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2012), pp. 655-661.

Hua Wang, Feiping Nie, Heng Huang. Robust and Discriminative Distance for Multi-Instance Learning, The 25th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012), pp. 2919-2924.

Deguang Kong, Chris Ding, Heng Huang, Haifeng Zhao. Multi-Label ReliefF and F-Statistic Feature Selections for Image Annotation, The 25th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012), pp. 2352-2359 .

Hua Wang, Heng Huang, Chris Ding, Feiping Nie. Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization. The 16th International Conference on Research in Computational Molecular Biology (RECOMB 2012), LNCS 7262, pp. 314-325.

Hua Wang, Heng Huang, Chris Ding. Function-Function Correlated Multi-Label Protein Function Prediction over Interaction Networks. The 16th International Conference on Research in Computational Molecular Biology (RECOMB 2012), LNCS 7262, pp. 302-313.

Nan Zhang, Liam O'Neill, Gautam Das, Xiuzhen Cheng, Heng Huang. No Silver Bullet: Identifying Security Vulnerabilities in Anonymization Protocols for Hospital Databases. International Journal of Healthcare Information Systems and Informatics (IJHISI), 7(4), pp. 49-59, 2012.

Hua Wang, Feiping Nie, Heng Huang, Sungeun Kim, Kwangsik Nho, Shannon Risacher, Andrew J Saykin, Li Shen, ADNI. Identifying Quantitative Trait Loci via Group-Sparse Multi-Task Regression and Feature Selection: An Imaging Genetics Study of the ADNI Cohort. Bioinformatics, Vol. 28, No. 2, pp. 229-237, 2012.

Kanishka Sircar, Heng Huang, Limei Hu, Yuexin Liu, Jasreman Dhillon, David Cogdell, Armen Aprikian, Eleni Efstathiou, Patricia Troncoso, Nora Navone and Wei Zhang. Integrative Molecular Profiling Reveals Asparagine Synthetase Is a Target in Castration-Resistant Prostate Cancer. The American Journal of Pathology, Vol. 180, Issue 3, pp. 895-903, 2012.

Kanishka Sircar, Heng Huang, Limei Hu, Yuexin Liu, Jasreman Dhillon, David Cogdell, Armen Aprikian, Eleni Efstathiou, Patricia Troncoso, Nora Navone and Wei Zhang. Mitosis Phase Enrichment with Identification of Mitotic Centromere-Associated Kinesin As a Therapeutic Target in Castration-Resistant Prostate Cancer, PLOS ONE, 7(2): e31259, 2012.

Hua Wang, Heng Huang, Monica Basco, Molly Lopez, Fillia Makedon. Self-taught learning via exponential family sparse coding for cost-effective patient thought record categorization, Personal and Ubiquitous Computing, Springer, pp. 1-9, 2012.


Xiao Cai, Feiping Nie, Heng Huang, Chris Ding. Feature Selection via l2,1-Norm Support Vector Machine. IEEE International Conference on Data Mining (ICDM 2011), pp. 91-100, (acceptance rate for full paper 12%).

Hua Wang, Feiping Nie, Heng Huang, Chris Ding. Nonnegative Matrix Tri-Factorization Based Simultaneous Clustering of Large-Scale Multi-Type Related Data. IEEE International Conference on Data Mining (ICDM 2011), pp. 774-783, (acceptance rate for full paper 12%).

Hua Wang, Heng Huang, Farhad Kamangar, Feiping Nie, Chris Ding. Maximum Margin Multi-Instance Learning. Neural Information Processing Systems Conference (NIPS 2011), pp. 1-9.

Hua Wang, Heng Huang, Chris Ding. Simultaneous Clustering of Multi-Type Relational Data via Symmetric Nonnegative Matrix Tri-Factorization. ACM Conference on Information and Knowledge Management (CIKM 2011), pp. 279-284.

Deguang Kong, Chris Ding, Heng Huang. Robust Nonnegative Matrix Factorization Using l2,1-Norm. ACM Conference on Information and Knowledge Management (CIKM 2011), pp. 673-682.

Hua Wang, Feiping Nie, Heng Huang, Shannon Risacher, Chris Ding, Andrew J Saykin, Li Shen, ADNI. A New Sparse Multi-Task Regression and Feature Selection Method to Identify Brain Imaging Predictors for Memory Performance. IEEE Conference on Computer Vision (ICCV 2011), pp. 557-562.

Feiping Nie, Hua Wang, Heng Huang, Chris Ding. Unsupervised and Semi-supervised Learning via l1-norm Graph. IEEE Conference on Computer Vision (ICCV 2011), pp. 2268-2273.

Hua Wang, Feiping Nie, Heng Huang, Chris Ding. Dyadic Transfer Learning for Cross-Domain Image Classification. IEEE Conference on Computer Vision (ICCV 2011), pp. 551-556.

Dijun Luo, Heng Huang, Chris Ding. Discriminative High Order SVD: Adaptive Tensor Subspace Selection for Image Classification, Clustering, and Retrieval. IEEE Conference on Computer Vision (ICCV 2011), pp. 1443-1448.

Hua Wang, Feiping Nie, Heng Huang, Shannon Risacher, Andrew J Saykin, Li Shen, ADNI. Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression. The 14th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2011), pp. 115-123, (acceptance rate for oral paper 4.15%, 34/819).

Dijun Luo, Feiping Nie, Chris Ding, Heng Huang. Multi-Subspace Representation and Discovery, ECML PKDD 2011, LNAI 6912, pp. 406-420, the Best Student Paper Runner-up Award in Machine Learning!

Dijun Luo, Chris Ding, Heng Huang. Graph Evolution via Social Diffusion Processes. ECML PKDD 2011, LNAI 6912, pp. 390-404, (acceptance rate 20%).

Dijun Luo, Chris Ding, Feiping Nie, Heng Huang. Cauchy Graph Embedding, The 28th International Conference on Machine Learning (ICML 2011), accepted to appear.

Hua Wang, Feiping Nie, Heng Huang. Learning Instance Specific Distance for Multi-Instance Classifications. Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), pp. 507-512.

Dijun Luo, Chris Ding, Heng Huang. Linear Discriminant Analysis: New Formulations and Overfit Analysis. Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), pp. 417-422.

Dijun Luo, Chris Ding, Heng Huang. Multi-Level Cluster Indicator Decomposition of Matrices and Tensors. Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), pp. 423-428.

Hua Wang, Heng Huang, Feiping Nie, Chris Ding. Cross-Language Web Page Classification via Dual Knowledge Transfer Using Nonnegative Matrix Tri-Factorization, The 34th Annual ACM SIGIR Conference (SIGIR 2011), pp. 933-942, (acceptance rate for regular paper 19.8%, 108/545).

Hua Wang, Feiping Nie, Heng Huang, Fillia Makedon. Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co-Clustering. The 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), pp. 1553-1558, (acceptance rate for oral presentation paper 17%, 227/1325).

Dijun Luo, Heng Huang. Ball Ranking Machine for Content-Based Multimedia Retrieval, The 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), pp. 1390-1395.

Dijun Luo, Chris Ding, Heng Huang. Cluster Indicator Decomposition for Efficient Matrix Factorization, The 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), pp. 1384-1389.

Feiping Nie, Heng Huang, Chris Ding, Dijun Luo, Hua Wang. Principal Component Analysis with Non-Greedy l1-Norm Maximization, The 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), pp. 1433-1438.

Hua Wang, Heng Huang, Chris Ding. Image Annotation Using Bi-Relational Graph of Images and Semantic Labels, The 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011), pp. 793-800.

Xiao Cai, Feiping Nie, Heng Huang, Farhad Kamangar. Heterogeneous Image Features Integration via Multi-Modal Spectral Clustering, The 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011), pp. 1977-1984.

Dijun Luo, Chris Ding, Heng Huang, Feiping Nie. Consensus Spectral Clustering, The IEEE International Conference on Data Engineering (ICDE 2011), pp. 1079-1090, (acceptance rate for regular paper 19.8%, 98/494).


Dijun Luo, Chris Ding, Heng Huang. Towards Structural Sparsity: An Explicit l2/l0 Approach, IEEE International Conference on Data Mining (ICDM 2010), pp. 344-353, (acceptance rate for regular paper 9%, 72/797), the best research paper runner up!

Feiping Nie, Heng Huang, Xiao Cai, Chris Ding. Efficient and Robust Feature Selection via Joint l2,1-Norms Minimization, Neural Information Processing Systems Conference (NIPS 2010), pp. 1813-1821.

Feiping Nie, Chris Ding, Dijun Luo, Heng Huang. Improved MinMax Cut Graph Clustering with Nonnegative Relaxation, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010), (acceptance rate 18%, 120/658), Vol. 2, pp. 451-467.

Hua Wang, Chris Ding, Heng Huang. Directed Graph Learning via High-Order Co-linkage Analysis, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010), (acceptance rate 18%, 120/658), Vol. 3, pp. 451-467.

Dijun Luo, Heng Huang, Chris Ding, Feiping Nie. On The Eigenvectors of p-Laplacian, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010), (acceptance rate 18%, 120/658).

Hua Wang, Chris Ding, Heng Huang. Multi-Label Linear Discriminant Analysis, The 11th European Conference on Computer Vision (ECCV 2010), Vol. 6316, pp. 126-139.

Hua Wang, Heng Huang, Chris Ding. Image Categorization Using Directed Graphs, The 11th European Conference on Computer Vision (ECCV 2010), Vol. 6313, pp. 762-775.

Hua Wang, Heng Huang, Chris Ding. Multi-Label Feature Transform, The 11th European Conference on Computer Vision (ECCV 2010), Vol. 6314, pp. 793-806.

Hua Wang, Heng Huang, Chris Ding. Discriminant Laplacian Embedding, Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2010), pp. 618-623.

Hua Wang, Chris Ding, Heng Huang. Multi-Label Classification: Inconsistency and Class Balanced K-Nearest Neighbor, Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2010), pp. 1264-1266.

Nha Nguyen, Heng Huang, Soontorn Oraintara, An Vo. Mass Spectrometry Data Processing Using Zero-Crossing Lines in Multi-Scale of Gaussian Derivative Wavelet, Bioinformatics, Vol. 26, pp. i659-i665, 2010.

An Vo, Nha Nguyen, Heng Huang. Solenoid and Non-solenoid Protein Recognition, Bioinformatics, Vol. 26, pp. i467-i473, 2010.

Dijun Luo, Heng Huang, Chris Ding, Feiping Nie. On The Eigenvectors of p-Laplacian, Machine Learning, Vol. 81, No. 1, pp. 37-51, 2010.

Nha Nguyen, Heng Huang, Soontorn Oraintara, An Vo. Stationary Wavelet Packet Transform and Dependent Laplacian Bivariate Shrinkage Estimator for Array-CGH Data Smoothing, Journal of Computational Biology, Vol. 17, No. 2, pp. 139-152, February, 2010.


Dijun Luo, Chris Ding, Heng Huang, Tao Li. Non-negative Laplacian Embedding, IEEE International Conference on Data Mining (ICDM 2009), pp. 337-346, (acceptance rate for regular paper 8.9%, 70/786).

Hua Wang, Heng Huang, Chris Ding. Image Annotation Using Multi-label Correlated Green's Function, IEEE Conference on Computer Vision (ICCV 2009), pp. 1-8.

Dijun Luo, Chris Ding, Heng Huang. Symmetric Two Dimensional Linear Discriminant Analysis (2DLDA), IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2009), pp. 1-8.

Dijun Luo, Heng Huang. Link Prediction of Multimedia Social Network via Unsupervised Face Recognition, ACM International Conference on Multimedia, pp. 805-808, 2009.

Vangelis Metsis, Heng Huang, Fillia Makedon, Aria Tzika. Heterogeneous Data Fusion to Type Brain Tumor Biopsies, the proceedings of the 5th IFIP Conference on Artificial Intelligence Applications & Innovations (AIAI 2009), pp. 233-240, 2009.

Nha Nguyen, Heng Huang, Soontorn Oraintara, An Vo. Peak Detection in Mass Spectrometry by Gabor Filters and Envelope Analysis, Journal of Bioinformatics and Computational Biology, Vol. 7, No. 3, pp. 547-569, 2009.

Fillia Makedon, Zhengyi Le, Heng Huang, Eric Becker, Dimitris Kosmopoulos. An Event Driven Framework for Assistive CPS Environments, ACM SIGBED Review, Vol. 6 (2), pp. 1-9, 2009.


Heng Huang, Chris Ding, Dijun Luo, Tao Li. Simultaneous Tensor Subspace Selection and Clustering: The Equivalence of High Order SVD and K-Means Clustering. The 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), pp. 327-335 (acceptance rate for long paper 9.8%, 50/510).

Nha Nguyen, Heng Huang, Soontorn Oraintara, An Vo. GABORLOCAL: Peak Detection In Mass Spectrum By Gabor Filters And Gaussian Local Maxima. Computational Systems Bioinformatics Conference (CSB 2008), pp. 85-96 (acceptance rate for full paper 22%).

Nha Nguyen, Heng Huang, Soontorn Oraintara, An Vo. Dependent Laplacian Bivariate Shrinkage Estimator For SWPT Based Array-CGH Data Smoothing. Computational Systems Bioinformatics Conference (CSB 2008), poster.

Heng Huang, Chris Ding. Robust Tensor Factorization Using R1 Norm. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), pp. 1-8.

Chris Ding, Heng Huang, Dijun Luo. Tensor Reduction Error Analysis -- Applications to Video Compression and Classification. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), pp. 1-8.

Heng Huang, Fillia Makedon. Statistical Shape Model Using High Dimensional Feature Selection, IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2008), pp. 1541-1544.

Heng Huang, Nha Nguyen, Soontorn Oraintara, An Vo. Array CGH Data Modeling and Smoothing in Stationary Wavelet Packet Transform Domain, BMC Genomics, Vol. 9 (S2:S17), 2008.

Heng Huang, Li Shen, James Ford, Yuhang Wang, Yurong Xu. Computational Issues in Biomedical Nanometrics and Nano-materials, Journal of Nano Research, Vol. 1, pp. 50-58, 2008.


Nha Nguyen, Heng Huang, Soontorn Oraintara, Yuhang Wang. Denoising of Array-Based DNA Copy Number Data Using The Dual-tree Complex Wavelet Transform. IEEE 7th International Symposium on Bioinformatics & Bioengineering (BIBE 2007), pp. 137-144 (acceptance rate for full paper < 12%, 60/500+).

Li Shen, Andrew J. Saykin, Moo K. Chung, Heng Huang. Morphometric Analysis of Hippocampal Shape in Mild Cognitive Impairment: An Imaging Genetics Study. IEEE 7th International Symposium on Bioinformatics & Bioengineering (BIBE 2007), pp. 211-217 (acceptance rate for full paper < 12%, 60/500+).

Nha Nguyen, Heng Huang, Soontorn Oraintara, An Vo. A New Smoothing Model for Analyzing Array CGH Data. IEEE 7th International Symposium on Bioinformatics & Bioengineering (BIBE 2007), pp. 1027-1034.

Heng Huang, Li Shen. Surface Harmonics for Shape Modeling. ICIP 2007: 14th IEEE International Conference on Image Processing, Volume 2, pp. 553-556.

Li Shen, Heng Huang, Fillia Makdeon, and Andrew J. Saykin. Efficient Registration of 3D SPHARM Surfaces. CRV 2007: Fourth Canadian Conference on Computer and Robot Vision, pp. 81-88 (acceptance rate for oral 24%, 25/103).

Chris Hawblitzel, Heng Huang, Lea Wittie, Juan Chen. A garbage-collecting typed assembly language. TLDI 2007, ACM SIGPLAN International Workshop on Types in Languages Design and Implementation, pp. 41-52.

Heng Huang, Fillia Makedon, Dan Popa, Harry Stephanou, James Ford, Yurong Xu. A Feature Extraction Method for Multimedia Data Analysis in Robot Wireless Sensor Networks. WIAMIS 2007: 8th International Workshop on Image Analysis for Multimedia Interactive Services, to appear.

Yurong Xu, James Ford, Fillia Makedon, Dan Popa, Heng Huang, Li Shen. In-home Localization for Home Care of Alzheimer's Disease Patients using Wireless Sensor Networks. International workshop on Pervasive Technologies for the support of Alzheimer's Disease and Related Disorders Sufferers, to appear.

Heng Huang, Li Shen, Nha Nguyen. Three Dimensional Models for Cardiac Bioelectricity Simulation: Cell to Organ, Simulation: Transactions of The Society for Modeling and Simulation International, Vol. 83, No. 4, pp. 321-327, 2007.

Heng Huang, Li Shen, Fillia Makedon, Andy Saykin, Justin Pearlman. A Novel Surface Registration Algorithm with Biomedical Modeling Applications, IEEE Transactions on Information Technology in BioMedicine,Volume 11, Issue 4, pp. 474-482, 2007.


Heng Huang, Lei Zhang, Dimitris Samaras, Li Shen, Fillia Makedon, Justin Pearlman. Hemispherical Harmonic Surface Description and Applications to Medical Image Analysis. TDPVT 2006, IEEE Symposium on 3D Data Processing, Visualization and Transmission, pp. 381-388 (acceptance rate for oral 15%, 28/183).

Heng Huang, Li Shen, Fillia Makedon, Justin Pearlman. A Spatio-Temporal Modeling Method for Shape RepresentationA Spatio-temporal Modeling for Shape Representation. TDPVT 2006, IEEE Symposium on 3D Data Processing, Visualization and Transmission, pp. 1034-1040.

Heng Huang, Li Shen, Rong Zhang, Fillia Makedon, Bruce Hettleman, Justin Pearlman. Fast Surface Reconstruction for Ischemic Cardiac Spatio-temporal Modeling. SPIE Medical Imaging 2006: Image Processing, Proceedings of SPIE, Volume 6144, pp. 1002-1009, 2006.

Li Shen, Andrew Saykin, Moo Chung, Heng Huang, James Ford, Fillia Makedon, Tara McHugh, Harker Rhodes. Morphometric Analysis of Genetic Variation in Hippocampal Shape in Mild Cognitive Impairment: Role of an IL-6 Promoter Polymorphism. CSB 2006: LSS Computational Systems Bioinformatics Conference, accepted to appear.

Li Shen, Heng Huang, Joshua Lu, James Ford, Ling Gao, Wei Zheng, Fillia Makedon, Justin Pearlman. Spatio-Temporal Analysis Tool for Modeling Pulmonary Nodules in MR Images. SPIE Medical Imaging 2006: Visualization, Image Guided Procedures, and Display, Proceedings of SPIE, Volume 6144, pp. 740-749, 2006.

Heng Huang, Li Shen, Fillia Makedon, Bruce Hettleman, Justin Pearlman. Cardiac Motion Analysis to Improve Pacing Site Selection in CRT, Academic Radiology, Elsevier Science, Volume 13, Issue 9, pp. 1124-1134, September 2006.


Heng Huang, Li Shen, Rong Zhang, Fillia Makedon, Bruce Hettleman, Justin Pearlman. Surface Alignment of 3D Spherical Harmonic Models: Application to Cardiac MRI Analysis. MICCAI 2005, 8th International Conference on Medical Image Computing and Computer Assisted Intervention.Lecture Notes in Computer Science LNCS 3749, Springer Verlag, pp. 67-74. (acceptance rate for oral 7%, 46/632)

Heng Huang, Li Shen, Rong Zhang, Fillia Makedon, Bruce Hettleman, Justin Pearlman. A Prediction Framework for Cardiac Resynchronization Therapy via 4D Cardiac Motion Analysis. MICCAI 2005, 8th International Conference on Medical Image Computing and Computer Assisted Intervention. Lecture Notes in Computer Science LNCS 3749, Springer Verlag, pp. 704-711.

Heng Huang, Rong Zhang, Fei Xiong, Fillia Makedon, Li Shen, Bruce Hettleman, Justin Pearlman. K-means+ Method for Improving Gene Selection for Classification of Microarray Data. CSB 2005, IEEE Computational Systems Bioinformatics Conference, pp. 110-111, 2005.

Heng Huang, Li Shen, Fillia Makedon, Sheng Zhang, Mark Greenberg, Ling Gao, Justin Pearlman. A Clustering-based Approach for Prediction of Cardiac Resynchronization Therapy. SAC 2005, 20th ACM Symposium on Applied Computing, pp. 260-266, 2005.

Heng Huang, Li Shen, James Ford, Fillia Makedon, Ling Gao, Justin Pearlman. Functional Analysis of Cardiac MR Images Using SPHARM Modeling. SPIE Medical Imaging 2005: Image Processing, Proceedings of SPIE, Volume 5747, pp. 1384-1391, 2005.

Fei Xiong, Heng Huang, James Ford, Fillia Makedon, Justin Pearlman. A New Test System for Stability Measurement of Marker Gene Selection in DNA Microarray Data Analysis. PCI 2005, 10th Panhellenic Conference on Informatics, Lecture Notes in Computer Science LNCS 3746, Springer Verlag, pp. 437-447.

Li Shen, Wei Zheng, Ling Gao, Heng Huang, Fillia Makedon, Justin Pearlman. Modeling Time-Intensity Profiles for Pulmonary Nodules in MR Images. EMBS 2005, The 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2005.

Li Shen, Ling Gao, Zhenwu Zhuang, Ebo DeMuinck, Heng Huang, Fillia Makedon, Justin Pearlman. An interactive 3D visualization and manipulation tool for effective assessment of angiogenesis and arteriogenesis using computed tomographic angiography. SPIE Medical Imaging 2005, San Diego, California, 12-17 February 2005.

Heng Huang, Li Shen, James Ford, Ling Gao, Justin Pearlman. Early lung cancer detection based on registered perfusion MRI. Journal of Oncology Reports, Volume 15, pp. 1080-1084, 2005.

Li Shen, Wei Zheng, Ling Gao, Heng Huang, Fillia Makedon, and Justin Pearlman. Spatio-Temporal Modeling of Lung Images for Cancer Detection. Journal of Oncology Reports, Volume 15, pp. 1085-1089, 2005.


Heng Huang, Fillia Makedon, Justin Pearlman, James Ford, Li Shen, Yuhang Wang, Ling Gao. Efficient Similarity Retrieval for Temporal Shape Sequences: A Case Study using Cardiac MR Images. Proceedings of 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Volume 2, pp. 3250-3253, 2004.

Heng Huang, Li Shen, Fillia Makedon, Ling Gao, Justin Pearlman. Three-Dimensional Analysis of Cardiac Magnetic Resonance Imaging using Spherical Harmonics Model. ACC'04, March 7-10, 2004, New Orleans, Supplement to the Journal of the American College of Cardiology, Volume 43, Number 5 (Supplement A), 2004.

Yuhang Wang, Fillia Makedon, James Ford, Heng Huang. A bipartite graph matching framework for finding correspondences between structural elements in two proteins. Proceedings of 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Volume 2, pp. 2972-2975, 2004.

Chris Hawblitzel, Edward Wei, Heng Huang, Eric Krupski, Lea Wittie. Low-Level Linear Memory Management. SPACE 2004, the Second ACM SIGPLAN Workshop on Semantics, Program Analysis, and Computing Environments for Memory Management, 2004.

Technical Reports

Guanling Chen, Heng Huang, Minkyong Kim. Mining Frequent and Periodic Association Patterns. Dartmouth CS Technical Report TR2005-550, May 2005.

Chris Hawblitzel, Heng Huang, Lea Wittie. Composing a Well-Typed Region. Dartmouth CS Technical Report TR2004-521, October 2004.

Heng Huang, Lea Wittie, Chris Hawblitzel. Formal Properties of Linear Memory Types. Dartmouth CS Technical Report TR2003-468, August 2003.

Heng Huang, Chris Hawblitzel. Proofs of Soundness and Strong Normalization for Linear Memory Types. Dartmouth CS Technical Report TR2002-437, November 2002.