Discriminative human action segmentation and recognition using semi-Markov model. - Qinfeng Shi; Li Wang 033; Li Cheng 001; Alexander J. Smola (CVPR, 2008)

Human Body Articulation for Action Recognition in Video Sequences. - Tuan Hue Thi; Sijun Lu; Jian Zhang 002; Li Cheng 001; Li Wang 033 (AVSS, 2009)

Human Action Recognition and Localization in Video Using Structured Learning of Local Space-Time Features. - Tuan Hue Thi; Jian Zhang 002; Li Cheng 001; Li Wang 033; Shinichi Satoh 001 (AVSS, 2010)

Human Action Recognition from Boosted Pose Estimation. - Li Wang 033; Li Cheng 001; Tuan Hue Thi; Jian Zhang 002 (DICTA, 2010)

Implicit Motion-Shape Model: A generic approach for action matching. - Tuan Hue Thi; Li Cheng 001; Jian Zhang 002; Li Wang 033 (ICIP, 2010)

Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets. - Mingkui Tan; Li Wang 033; Ivor W. Tsang (ICML, 2010)

Weakly Supervised Action Recognition Using Implicit Shape Models. - Tuan Hue Thi; Li Cheng 001; Jian Zhang 002; Li Wang 033; Shinichi Satoh 001 (ICPR, 2010)

Human Action Segmentation and Recognition Using Discriminative Semi-Markov Models. - Qinfeng Shi; Li Cheng 001; Li Wang 033; Alexander J. Smola (Int. J. Comput. Vis., 2011)

Elastic Sequence Correlation for Human Action Analysis. - Li Wang 033; Li Cheng 001; Liang Wang 001 (IEEE Trans. Image Process., 2011)

Convex Matching Pursuit for Large-Scale Sparse Coding and Subset Selection. - Mingkui Tan; Ivor W. Tsang; Li Wang 033; Xinming Zhang (AAAI, 2012)

Towards Large-scale and Ultrahigh Dimensional Feature Selection via Feature Generation - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (CoRR, 2012)

Integrating local action elements for action analysis. - Tuan Hue Thi; Li Cheng 001; Jian Zhang 002; Li Wang 033; Shinichi Satoh 001 (Comput. Vis. Image Underst., 2012)

Structured learning of local features for human action classification and localization. - Tuan Hue Thi; Li Cheng 001; Jian Zhang 002; Li Wang 033; Shinichi Satoh 001 (Image Vis. Comput., 2012)

Is Matching Pursuit Solving Convex Problems? - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (CoRR, 2013)

Minimax Sparse Logistic Regression for Very High-Dimensional Feature Selection. - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (IEEE Trans. Neural Networks Learn. Syst., 2013)

Riemannian Pursuit for Big Matrix Recovery. - Mingkui Tan; Ivor W. Tsang; Li Wang 033; Bart Vandereycken; Sinno Jialin Pan (ICML, 2014)

Recognizing flu-like symptoms from videos. - Tuan Hue Thi; Li Wang 033; Ning Ye; Jian Zhang 002; Sebastian Maurer-Stroh; Li Cheng 001 (BMC Bioinform., 2014)

Towards ultrahigh dimensional feature selection for big data. - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (J. Mach. Learn. Res., 2014)

Parallel Hierarchical Clustering in Linearithmic Time for Large-Scale Sequence Analysis. - Qi Mao 001; Wei Zheng 010; Li Wang 033; Yunpeng Cai; Volker Mai; Yijun Sun (ICDM, 2015)

Dimensionality Reduction Via Graph Structure Learning. - Qi Mao 001; Li Wang 033; Steve Goodison; Yijun Sun (KDD, 2015)

SimplePPT: A Simple Principal Tree Algorithm. - Qi Mao 001; Le Yang; Li Wang 033; Steve Goodison; Yijun Sun (SDM, 2015)

A Novel Regularized Principal Graph Learning Framework on Explicit Graph Representation. - Qi Mao 001; Li Wang 033; Ivor W. Tsang; Yijun Sun (CoRR, 2015)

Generalized Multiple Kernel Learning With Data-Dependent Priors. - Qi Mao 001; Ivor W. Tsang; Shenghua Gao; Li Wang 033 (IEEE Trans. Neural Networks Learn. Syst., 2015)

Matching Pursuit LASSO Part I: Sparse Recovery Over Big Dictionary. - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (IEEE Trans. Signal Process., 2015)

Matching Pursuit LASSO Part II: Applications and Sparse Recovery Over Batch Signals. - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (IEEE Trans. Signal Process., 2015)

Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data. - Mingkui Tan; Yan Yan 006; Li Wang 033; Anton van den Hengel; Ivor W. Tsang; Qinfeng (Javen) Shi (AAAI, 2016)

Face Recognition via Active Annotation and Learning. - Hao Ye 005; Weiyuan Shao; Hong Wang 014; Jianqi Ma; Li Wang 033; Yingbin Zheng; Xiangyang Xue 001 (ACM Multimedia, 2016)

Probabilistic Dimensionality Reduction via Structure Learning. - Li Wang 033 (CoRR, 2016)

Latent Smooth Skeleton Embedding. - Li Wang 033; Qi Mao 001; Ivor W. Tsang (AAAI, 2017)

On the Flatness of Loss Surface for Two-layered ReLU Networks. - Jiezhang Cao; Qingyao Wu; Yuguang Yan; Li Wang 033; Mingkui Tan (ACML, 2017)

UA-DETRAC 2017: Report of AVSS2017 & IWT4S Challenge on Advanced Traffic Monitoring. - Siwei Lyu; Ming-Ching Chang; Dawei Du; Longyin Wen; Honggang Qi; Yuezun Li; Yi Wei 006; Lipeng Ke; Tao Hu 011; Marco Del Coco; Pierluigi Carcagnì; Dmitriy Anisimov; et al. (AVSS, 2017)

Evolving boxes for fast vehicle detection. - Li Wang 033; Yao Lu; Hong Wang 014; Yingbin Zheng; Hao Ye 005; Xiangyang Xue 001 (ICME, 2017)

A unified probabilistic framework for robust manifold learning and embedding. - Qi Mao 001; Li Wang 033; Ivor W. Tsang (Mach. Learn., 2017)

Principal Graph and Structure Learning Based on Reversed Graph Embedding. - Qi Mao 001; Li Wang 033; Ivor W. Tsang; Yijun Sun (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Exploring latent structures of Alzheimer's disease via structure learning. - Dajiang Zhu; Li Wang 033 (ISBI, 2018)

Crowd Counting with Density Adaption Networks. - Li Wang 033; Weiyuan Shao; Yao Lu; Hao Ye 005; Jian Pu; Yingbin Zheng (CoRR, 2018)

Learning Multiviewpoint Context-Aware Representation for RGB-D Scene Classification. - Yingbin Zheng; Hao Ye 005; Li Wang 033; Jian Pu (IEEE Signal Process. Lett., 2018)

Arbitrary-Oriented Scene Text Detection via Rotation Proposals. - Jianqi Ma; Weiyuan Shao; Hao Ye 005; Li Wang 033; Hong Wang 014; Yingbin Zheng; Xiangyang Xue 001 (IEEE Trans. Multim., 2018)

CODA: Counting Objects via Scale-Aware Adversarial Density Adaption. - Li Wang 033; Yongbo Li; Xiangyang Xue 001 (ICME, 2019)

Analyzing Mild Cognitive Impairment Progression via Multi-view Structural Learning. - Li Wang 033; Paul M. Thompson; Dajiang Zhu (IPMI, 2019)

Accessing Latent Connectome of Mild Cognitive Impairment via Discriminant Structure Learning. - Li Wang 033; Lu Zhang 050; Dajiang Zhu (ISBI, 2019)

A Cascaded Multi-modality Analysis in Mild Cognitive Impairment. - Lu Zhang 050; Akib Zaman 001; Li Wang 033; Jingwen Yan; Dajiang Zhu (MLMI@MICCAI, 2019)

Probabilistic Structure Learning for EEG/MEG Source Imaging with Hierarchical Graph Prior. - Feng Liu 011; Li Wang 033; Yifei Lou; Ren-Cang Li; Patrick L. Purdon (CoRR, 2019)

Large-Scale Semi-Supervised Learning via Graph Structure Learning over High-Dense Points. - Zitong Wang; Li Wang 033; Raymond H. Chan; Tieyong Zeng (CoRR, 2019)

Probabilistic Dimensionality Reduction via Structure Learning. - Li Wang 033; Qi Mao 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Learning Latent Structure Over Deep Fusion Model of Mild Cognitive Impairment. - Li Wang 033; Lu Zhang 050; Dajiang Zhu (ISBI, 2020)

Jointly Analyzing Alzheimer's Disease Related Structure-Function Using Deep Cross-Model Attention Network. - Lu Zhang 050; Li Wang 033; Dajiang Zhu (ISBI, 2020)

Recovering Brain Structural Connectivity from Functional Connectivity via Multi-GCN Based Generative Adversarial Network. - Lu Zhang 050; Li Wang 033; Dajiang Zhu (MICCAI (7), 2020)

Multi-view Orthonormalized Partial Least Squares: Regularizations and Deep Extensions. - Li Wang 033; Ren-Cang Li; Wen-Wei Lin (CoRR, 2020)

Uncorrelated Semi-paired Subspace Learning. - Li Wang 033; Lei-Hong Zhang; Chungen Shen; Ren-Cang Li (CoRR, 2020)

Spectral norm of a symmetric tensor and its computation. - Shmuel Friedland; Li Wang 033 (Math. Comput., 2020)

Orthogonal canonical correlation analysis and applications. - Li Wang 033; Lei-Hong Zhang; Zhaojun Bai; Ren-Cang Li (Optim. Methods Softw., 2020)

Learning Low-Dimensional Latent Graph Structures: A Density Estimation Approach. - Li Wang 033; Ren-Cang Li (IEEE Trans. Neural Networks Learn. Syst., 2020)

Depth-Conditioned Dynamic Message Propagation for Monocular 3D Object Detection. - Li Wang 033; Liang Du 004; Xiaoqing Ye; Yanwei Fu 001; Guodong Guo; Xiangyang Xue 001; Jianfeng Feng; Li Zhang 040 (CVPR, 2021)

Progressive Coordinate Transforms for Monocular 3D Object Detection. - Li Wang 033; Li Zhang 040; Yi Zhu 001; Zhi Zhang 005; Tong He 002; Mu Li 003; Xiangyang Xue 001 (NeurIPS, 2021)

Representing Alzheimer's Disease Progression via Deep Prototype Tree. - Lu Zhang 050; Li Wang 033; Dajiang Zhu (CoRR, 2021)

On Generalizing Trace Minimization. - Xin Liang 004; Li Wang 033; Lei-Hong Zhang; Ren-Cang Li (CoRR, 2021)

Deep Fusion of Brain Structure-Function in Mild Cognitive Impairment. - Lu Zhang 050; Li Wang 033; Jean Gao; Shannon L. Risacher; Jingwen Yan; Gang Li 001; Tianming Liu 001; Dajiang Zhu (Medical Image Anal., 2021)

An Improved Boundary-Aware U-Net for Ore Image Semantic Segmentation. - Wei Wang; Qing Li 015; Chengyong Xiao; Dezheng Zhang; Lei Miao; Li Wang 033 (Sensors, 2021)

Probabilistic Structure Learning for EEG/MEG Source Imaging With Hierarchical Graph Priors. - Feng Liu 011; Li Wang 033; Yifei Lou; Ren-Cang Li; Patrick L. Purdon (IEEE Trans. Medical Imaging, 2021)

Multi-Material Decomposition for Single Energy CT Using Material Sparsity Constraint. - Yi Xue; Wenjian Qin; Chen Luo; Pengfei Yang; Yangkang Jiang; Tiffany Tsui; Hongjian He; Li Wang 033; Jiale Qin; Yaoqin Xie; Tianye Niu (IEEE Trans. Medical Imaging, 2021)

Probabilistic Semi-Supervised Learning via Sparse Graph Structure Learning. - Li Wang 033; Raymond H. Chan; Tieyong Zeng (IEEE Trans. Neural Networks Learn. Syst., 2021)

Exploring Latent Sparse Graph for Large-Scale Semi-supervised Learning. - Zitong Wang; Li Wang 033; Raymond H. Chan; Tieyong Zeng (ECML/PKDD (4), 2022)

A self-consistent-field iteration for MAXBET with an application to multi-view feature extraction. - Xijun Ma; Chungen Shen; Li Wang 033; Lei-Hong Zhang; Ren-Cang Li (Adv. Comput. Math., 2022)

Orthogonal multi-view analysis by successive approximations via eigenvectors. - Li Wang 033; Lei-Hong Zhang; Chungen Shen; Ren-Cang Li (Neurocomputing, 2022)

Predicting brain structural network using functional connectivity. - Lu Zhang 050; Li Wang 033; Dajiang Zhu; Alzheimer's Disease Neuroimaging Initiative (Medical Image Anal., 2022)

A comparison of methods to harmonize cortical thickness measurements across scanners and sites. - Delin Sun; Gopalkumar Rakesh; Courtney C. Haswell; Mark W. Logue; C. Lexi Baird; Erin O'Leary; Andrew S. Cotton; Hong Xie; Marijo B. Tamburrino; Tian Chen; Emily L. Dennis; Neda Jahanshad; et al. (NeuroImage, 2022)

Maximizing sum of coupled traces with applications. - Li Wang 033; Lei-Hong Zhang; Ren-Cang Li (Numerische Mathematik, 2022)

A Self-Consistent-Field Iteration for Orthogonal Canonical Correlation Analysis. - Lei-Hong Zhang; Li Wang 033; Zhaojun Bai; Ren-Cang Li (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

A Scalable Algorithm for Large-Scale Unsupervised Multi-View Partial Least Squares. - Li Wang 033; Ren-Cang Li (IEEE Trans. Big Data, 2022)

Deep Tensor CCA for Multi-View Learning. - Hok Shing Wong; Li Wang 033; Raymond H. Chan; Tieyong Zeng (IEEE Trans. Big Data, 2022)

Human Identification at a Distance: Challenges, Methods and Results on HID 2023. - Shiqi Yu 001; Chenye Wang; Yuwei Zhao; Li Wang 033; Ming Wang; Qing Li 015; Wenlong Li; Runsheng Wang; Yongzhen Huang; Liang Wang 001; Yasushi Makihara; Md Atiqur Rahman Ahad (IJCB, 2023)

ImpDet: Exploring Implicit Fields for 3D Object Detection. - Xuelin Qian; Li Wang 033; Yi Zhu 001; Li Zhang 040; Yanwei Fu 001; Xiangyang Xue 001 (WACV, 2023)

Exploring the Influence of Information Entropy Change in Learning Systems. - Xiaowei Yu; Yao Xue; Lu Zhang 050; Li Wang 033; Tianming Liu 001; Dajiang Zhu (CoRR, 2023)

Trace ratio optimization with an application to multi-view learning. - Li Wang 033; Lei-Hong Zhang; Ren-Cang Li (Math. Program., 2023)

Multiview Orthonormalized Partial Least Squares: Regularizations and Deep Extensions. - Li Wang 033; Ren-Cang Li; Wen-Wei Lin (IEEE Trans. Neural Networks Learn. Syst., 2023)

Density-Based Distance Preserving Graph: Theoretical and Practical Analyses. - Li Wang 033; Haian Yin; Jin Zhang 002 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium. - Xi Zhu; Yoojean Kim; Orren Ravid; Xiaofu He; Benjamin Suarez-Jimenez; Sigal Zilcha-Mano; Amit Lazarov; Seonjoo Lee; Chadi G. Abdallah; Michael Angstadt; Christopher L. Averill; C. Lexi Baird; et al. (NeuroImage, 2023)

A Comparative Study of Deep Reinforcement Learning for Crop Production Management. - Joseph Balderas; Dong Chen 016; Yanbo Huang; Li Wang 033; Ren-Cang Li (CoRR, 2024)

Adversarial Purification by Consistency-aware Latent Space Optimization on Data Manifolds. - Shuhai Zhang; Jiahao Yang; Hui Luo 002; Jie Chen; Li Wang 033; Feng Liu 003; Bo Han 003; Mingkui Tan (CoRR, 2024)

Differential Equation-Constrained Optimization with Stochasticity. - Qin Li 007; Li Wang 033; Yunan Yang (SIAM/ASA J. Uncertain. Quantification, 2024)

An NEPv Approach for Feature Selection via Orthogonal OCCA with the (2,1)-norm Regularization. - Li Wang 033; Lei-Hong Zhang; Ren-Cang Li (CoRR, 2025)