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ORCIDMing Li 0065
李明
Person information
- unicode name: 李明
- affiliation: Zhejiang Normal University, Department of Computer Science, Jinhua, China
- affiliation: South China Normal University, School of Information Technology in Education, Guangzhou, China
- affiliation (PhD): La Trobe University, Department of Computer Science and Information Technology, Melbourne, VIC , Australia
Other persons with the same name
- Ming Li — disambiguation page
- Ming Li 0001
![[0000-0002-2157-2775]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-2157-2775")
— University of Waterloo, ON, Canada (and 3 more) - Ming Li 0002 — East China Normal University, Shanghai, China (and 1 more)
- Ming Li 0003 (aka: Ming (Fred) Li) — University of Arizona, Tucson, AZ, USA (and 2 more)
- Ming Li 0004 — Xidian University, National Key Lab of Radar Signal Processing, Xi'an, China
- Ming Li 0005 — Nanjing University, National Key Laboratory for Novel Software Technology, China
- Ming Li 0006 — University of Texas at Arlington, TX, USA (and 2 more)
- Ming Li 0007 — California State University, Fresno, CA, USA (and 1 more)
- Ming Li 0008 — Worcester Polytechnic Institute, MA, USA
- Ming Li 0009 — IBM T. J. Watson Research Center, Yorktown Heights, NY, USA (and 1 more)
- Ming Li 0010 — Deakin University, VIC, Australia
- Ming Li 0011 — Dalian University of Technology, School of Information and Communication Engineering, China (and 2 more)
- Ming Li 0012 — Taiyuan University of Technology, College of Mathematics, China (and 1 more)
- Ming Li 0013 — China University of Mining & Technology, Xuzhou, China
- Ming Li 0014 — Unilever Corporate Research, Sharnbrook, Bedford, UK
- Ming Li 0015 — Lanzhou University of Technology, China
- Ming Li 0016 — RWTH Aachen University, Germany
- Ming Li 0017 — Zhejiang University, State Key Laboratory of CAD&CG, China
- Ming Li 0018 — Max-Planck-Institut für Informatik, Saarbrücken, Germany
- Ming Li 0019 — Carleton University, Ottawa, ON, Canada
- Ming Li 0020 — Google (and 1 more)
- Ming Li 0021 — Oracle (and 1 more)
- Ming Li 0022 — Vanderbilt University, Department of Biostatistics, Nashville, TN, USA
- Ming Li 0023 — Simon Fraser University, Burnaby, BC, Canada
- Ming Li 0024 — Concordia University, Department of Economics, Montreal, QC, Canada
- Ming Li 0025 — Chinese Academy of Sciences, Institute of Semiconductors, China (and 1 more)
- Ming Li 0026 — Duke Kunshan University, Data Science Research Center, China (and 3 more)
- Ming Li 0028 — National University of Defense Technology, College of Mechatronic Engineering and Automation, Changsha, China
- Ming Li 0029 — Beihang University, School of Automation Science and Electrical Engineering, Beijing, China (and 2 more)
- Ming Li 0030 — Auburn University MRI Research Center, Auburn, USA
- Ming Li 0031 — China University of Mining and Technology, School of Computer Science and Technology, Xuzhou, China
- Ming Li 0032 — Heidelberg University, Institute of Geography, Germany
- Ming Li 0033 — Chinese Academy of Sciences, Institute of Information Engineering, State Key Laboratory of Information Security, Beijing, China
- Ming Li 0034 — Beihang University, Institute of Solid Mechanics, Beijing, China
- Ming Li 0035 — Aalto University, Department of Computer Science, Espoo, Finland
- Ming Li 0036 — Honghe University, Department of Mathematics, Mengzi, Yunnan, China
- Ming Li 0037 — Wuhan University, State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, China
- Ming Li 0038 — Second Military Medical University, Changhai Hospital, Department of Orthopaedics, Shanghai, China
- Ming Li 0039 — China Jiliang University, Department of Mathematics, Hangzhou, China
- Ming Li 0040 — Nanchang University, ISST, China (and 1 more)
- Ming Li 0041 — Tianjin Normal University, Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, China (and 1 more)
- Ming Li 0042 — Hamburg University of Technology, Germany
- Ming Li 0043 — Unilever China (and 1 more)
- Ming Li 0044 — Colorado School of Mines, Department of Electrical Engineering and Computer Science, Golden, CO, USA
- Ming Li 0045 — Shanghai Jiao Tong University, Institute of Image Processing and Pattern Recognition, China
- Ming Li 0046 — Yanshan University, College of Electrical Engineering, Qinhuangdao, China
- Ming Li 0047 — Beijing Jiaotong University, School of Electronic and Information Engineering, China
- Ming Li 0048 — Sun Yat-sen University, School of Geography and Planning, Guangzhou, China
- Ming Li 0049 — Jinan University, College of Information Science and Technology, China
- Ming Li 0051 — China University of Petroleum, School of Economics and Management, Beijing, China
- Ming Li 0052 — National Institutes of Health, Center for Interventional Oncology / National Heart, Lung, and Blood Institute, Bethesda, MD, USA (and 1 more)
- Ming Li 0053 — Macquarie University, Sydney, NSW, Australia (and 3 more)
- Ming Li 0054 — Beihang University, School of Transportation Science and Engineering / Beijing Advanced Innovation Center for Big Data and Brain Computing, Beijing, China
- Ming Li 0055 — Hong Kong Polytechnic University, Department of Industrial and Systems Engineering, Hong Kong (and 2 more)
- Ming Li 0056 — Nanchang Hangkong University, MOE Key Laboratory of Nondestructive Testing, China (and 1 more)
- Ming Li 0057 — Ocean University of China, College of Engineering, Department of Automation, Qingdao, China (and 1 more)
- Ming Li 0058 — Shenyang University of Technology, School of Electrical Engineering, China
- Ming Li 0059 — National University of Defense Technology, College of Meteorology and Oceanography, Nanjing, China
- Ming Li 0060 — Harbin Engineering University, College of Computer Science and Technology, China
- Ming Li 0061 — Rizhao People's Hospital, Department of Nuclear Medicine, China
- Ming Li 0062 — CRRC Tangshan Company, Ltd., Tangshan, China
- Ming Li 0063 — Harbin Institute of Technology, Communication Research Center, China
- Ming Li 0064 — Beijing Institute of Technology, State Key Laboratory of Explosion Science and Technology, China
- Ming Li 0066 — National University of Defense Technology, College of Electronic Science and Technology, State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Changsha, China
- Ming Li 0067 — Lappeenranta University of Technology, LUT, Laboratory of Intelligent Machines, Department of Mechanical Engineering, Finland
- Ming Li 0068 — University of Amsterdam, IRLab, Netherlands (and 1 more)
- Ming Li 0069 — Nanjing University, School of Electronic Science and Engineering, China
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2020 – today
- 2024
[j37]Yu-Ting Chen, Ming Li, Mutlu Cukurova, Morris Siu-Yung Jong:
Incorporation of peer-feedback into the pedagogical use of spherical video-based virtual reality in writing education. Br. J. Educ. Technol. 55(2): 519-540 (2024)- [j36]Ming Li, Xiaosheng Zhuang, Lu Bai, Weiping Ding:
Multimodal graph learning based on 3D Haar semi-tight framelet for student engagement prediction. Inf. Fusion 105: 102224 (2024) - [j35]Siqi Liu, Hailiang Ye, Bing Yang, Ming Li, Feilong Cao:
A joint parcellation and boundary network with multi-rate-shared dilated graph attention for cortical surface parcellation. Medical Biol. Eng. Comput. 62(2): 537-549 (2024) - [j34]Lixin Cui, Ming Li, Lu Bai, Yue Wang, Jing Li, Yanchao Wang, Zhao Li, Yunwen Chen, Edwin R. Hancock:
QBER: Quantum-based Entropic Representations for un-attributed graphs. Pattern Recognit. 145: 109877 (2024) - [j33]Chunya Zou, Andi Han, Lequan Lin, Ming Li, Junbin Gao:
A Simple Yet Effective Framelet-Based Graph Neural Network for Directed Graphs. IEEE Trans. Artif. Intell. 5(4): 1647-1657 (2024) - [j32]Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R. Hancock:
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus. IEEE Trans. Knowl. Data Eng. 36(2): 475-489 (2024) - [j31]Yuting Chen, Ming Li, Changqin Huang, Mutlu Cukurova, Qing Ma:
A Systematic Review of Research on Immersive Technology-Enhanced Writing Education: The Current State and a Research Agenda. IEEE Trans. Learn. Technol. 17: 919-938 (2024) - [c11]Zhao Li, Guoqi Ren, Yongchun Gu, Siwei Zhou, Xuanwu Liu, Jiaming Huang, Ming Li:
Real-time E-bike Route Planning with Battery Range Prediction. WSDM 2024: 1070-1073 - 2023
- [j30]Ming Li, Yuting Chen, Chang-Qin Huang, Gwo-Jen Hwang, Mutlu Cukurova:
From motivational experience to creative writing: A motivational AR-based learning approach to promoting Chinese writing performance and positive writing behaviours. Comput. Educ. 202: 104844 (2023) - [j29]Hailiang Ye, Yuzhi Song, Ming Li, Feilong Cao:
A new deep graph attention approach with influence and preference relationship reconstruction for rate prediction recommendation. Inf. Process. Manag. 60(5): 103439 (2023) - [j28]Xiaoyong Mei, Yougen Zhou, Chenjing Zhu, Mengting Wu, Ming Li, Shirui Pan:
A disentangled linguistic graph model for explainable aspect-based sentiment analysis. Knowl. Based Syst. 260: 110150 (2023) - [j27]Changqin Huang, Junling Zhang, Xuemei Wu, Yi Wang, Ming Li, Xiaodi Huang:
TeFNA: Text-centered fusion network with crossmodal attention for multimodal sentiment analysis. Knowl. Based Syst. 269: 110502 (2023) - [j26]Xuebin Zheng, Bingxin Zhou, Ming Li, Yu Guang Wang, Junbin Gao:
MathNet: Haar-like wavelet multiresolution analysis for graph representation learning. Knowl. Based Syst. 273: 110609 (2023) - [j25]Jiaxing Miao, Feilong Cao, Hailiang Ye, Ming Li, Bing Yang:
Revisiting graph neural networks from hybrid regularized graph signal reconstruction. Neural Networks 157: 444-459 (2023) - [j24]Changqin Huang, Ming Li, Feilong Cao, Hamido Fujita, Zhao Li, Xindong Wu:
Are Graph Convolutional Networks With Random Weights Feasible? IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 2751-2768 (2023) - [j23]Jiaxing Miao, Feilong Cao, Ming Li, Bing Yang, Hailiang Ye:
Triplet teaching graph contrastive networks with self-evolving adaptive augmentation. Pattern Recognit. 142: 109687 (2023) - [j22]Ming Li, Lin Zhang, Lixin Cui, Lu Bai, Zhao Li, Xindong Wu:
BLoG: Bootstrapped graph representation learning with local and global regularization for recommendation. Pattern Recognit. 144: 109874 (2023) - [j21]Bing Yang, Hailiang Ye, Ming Li, Feilong Cao, Shirui Pan:
GoLoG: Global-to-Local Decoupling Graph Network With Joint Optimization for Hyperspectral Image Classification. IEEE Trans. Geosci. Remote. Sens. 61: 1-14 (2023) - [j20]Zhihui Wang, Zhiyuan Li, Jiaxu Leng, Ming Li, Lu Bai:
Multiple Pedestrian Tracking With Graph Attention Map on Urban Road Scene. IEEE Trans. Intell. Transp. Syst. 24(8): 8567-8579 (2023) - [j19]Yangjie Qin, Ming Li, Jia Zhu:
Privacy-preserving federated learning framework in multimedia courses recommendation. Wirel. Networks 29(4): 1535-1544 (2023) - [c10]Ming Li, Sho Sonoda, Feilong Cao, Yu Guang Wang, Jiye Liang:
How Powerful are Shallow Neural Networks with Bandlimited Random Weights? ICML 2023: 19960-19981 - [c9]Xinhong Meng, Meng Hu, Hailiang Ye, Ming Li, Feilong Cao:
A Global-and-Local Feature Fusion Network for Point Cloud Classification. ICMLC 2023: 89-96 - [c8]Shiyu Liu, Linsen Wei, Shaogao Lv, Ming Li:
Stability and Generalization of lp-Regularized Stochastic Learning for GCN. IJCAI 2023: 5685-5693 - [i19]Lixin Cui, Ming Li, Yue Wang, Lu Bai, Edwin R. Hancock:
AERK: Aligned Entropic Reproducing Kernels through Continuous-time Quantum Walks. CoRR abs/2303.03396 (2023) - [i18]Jianfei Li, Ruigang Zheng, Han Feng, Ming Li, Xiaosheng Zhuang:
Permutation Equivariant Graph Framelets for Heterophilous Graph Learning. CoRR abs/2306.04265 (2023) - 2022
- [j18]Kaixuan Yao, Jiye Liang, Jianqing Liang, Ming Li, Feilong Cao:
Multi-view graph convolutional networks with attention mechanism. Artif. Intell. 307: 103708 (2022) - [j17]Yuting Chen, Ming Li, Chang-Qin Huang, Zhongmei Han, Gwo-Jen Hwang, Gang Yang:
Promoting deep writing with immersive technologies: An SVVR-supported Chinese composition writing approach for primary schools. Br. J. Educ. Technol. 53(6): 2071-2091 (2022) - [j16]Yuzhi Song, Hailiang Ye, Ming Li, Feilong Cao:
Deep multi-graph neural networks with attention fusion for recommendation. Expert Syst. Appl. 191: 116240 (2022) - [j15]Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao:
Embedding graphs on Grassmann manifold. Neural Networks 152: 322-331 (2022) - [j14]Yuehua Liu, Wenjin Yu, Tharam S. Dillon, Wenny Rahayu, Ming Li:
Empowering IoT Predictive Maintenance Solutions With AI: A Distributed System for Manufacturing Plant-Wide Monitoring. IEEE Trans. Ind. Informatics 18(2): 1345-1354 (2022) - [c7]Ming Li, Giorgio Gnecco, Marcello Sanguineti:
Deeper Insights into Neural Nets with Random Weights. AI 2022: 129-140 - [c6]Junwei Zhang, Zhao Li, Hao Peng, Ming Li, Xiaofen Wang:
Feedforward Neural Network Reconstructed from High-order Quantum Systems. IJCNN 2022: 1-8 - [c5]Junwei Zhang, Zhao Li, Jianmao Xiao, Ming Li:
Neural Network Model Reconstructed from Entangled Quantum States. IJCNN 2022: 1-8 - [i17]Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao:
Embedding Graphs on Grassmann Manifold. CoRR abs/2205.15068 (2022) - [i16]Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R. Hancock:
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus. CoRR abs/2206.07472 (2022) - [i15]Lu Bai, Lixin Cui, Yue Wang, Ming Li, Edwin R. Hancock:
HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification. CoRR abs/2211.02904 (2022) - 2021
- [j13]Zhihui Wang, Ming Li, Yu Lu, Yongtang Bao, Zhe Li, Jianli Zhao:
Effective multiple pedestrian tracking system in video surveillance with monocular stationary camera. Expert Syst. Appl. 178: 114992 (2021) - [j12]Changqin Huang, Ming Li, Dianhui Wang:
Stochastic configuration network ensembles with selective base models. Neural Networks 137: 106-118 (2021) - [j11]Ming Li, Dianhui Wang:
2-D Stochastic Configuration Networks for Image Data Analytics. IEEE Trans. Cybern. 51(1): 359-372 (2021) - [j10]Quoc Thong Le Gia, Ming Li, Yu Guang Wang:
Algorithm 1018: FaVeST - Fast Vector Spherical Harmonic Transforms. ACM Trans. Math. Softw. 47(4): 39:1-39:24 (2021) - [c4]Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montúfar:
How Framelets Enhance Graph Neural Networks. ICML 2021: 12761-12771 - [i14]Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Liò, Ming Li, Guido Montúfar:
How Framelets Enhance Graph Neural Networks. CoRR abs/2102.06986 (2021) - [i13]Yizhen Zheng, Ming Jin, Shirui Pan, Yuan-Fang Li, Hao Peng, Ming Li, Zhao Li:
Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming. CoRR abs/2111.10698 (2021) - 2020
- [j9]Zhengyang Wu, Ming Li, Yong Tang, Qingyu Liang:
Exercise recommendation based on knowledge concept prediction. Knowl. Based Syst. 210: 106481 (2020) - [j8]Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang:
Fast Haar Transforms for Graph Neural Networks. Neural Networks 128: 188-198 (2020) - [j7]Daniel Vidali Fryer, Ming Li, Andriy Olenko:
rcosmo: R Package for Analysis of Spherical, HEALPix and Cosmological Data. R J. 12(1): 206 (2020) - [j6]Tao He, Changqin Huang, Ming Li, Yuqiong Zhou, Shihua Li:
Social participation of the elderly in China: The roles of conventional media, digital access and social media engagement. Telematics Informatics 48: 101347 (2020) - [c3]Yuguang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan:
Haar Graph Pooling. ICML 2020: 9952-9962 - [c2]Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Liò:
Path Integral Based Convolution and Pooling for Graph Neural Networks. NeurIPS 2020 - [i12]Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Lió:
Path Integral Based Convolution and Pooling for Graph Neural Networks. CoRR abs/2006.16811 (2020) - [i11]Xuebin Zheng, Bingxin Zhou, Ming Li, Yu Guang Wang, Junbin Gao:
Graph Neural Networks with Haar Transform-Based Convolution and Pooling: A Complete Guide. CoRR abs/2007.11202 (2020) - [i10]Sho Sonoda, Ming Li, Feilong Cao, Changqin Huang, Yu Guang Wang:
On the Approximation Lower Bound for Neural Nets with Random Weights. CoRR abs/2008.08427 (2020)
2010 – 2019
- 2019
- [j5]Ming Li, Changqin Huang, Dianhui Wang, Qintai Hu, Jia Zhu, Yong Tang:
Improved randomized learning algorithms for imbalanced and noisy educational data classification. Computing 101(6): 571-585 (2019) - [j4]Ming Li, Changqin Huang, Dianhui Wang:
Robust stochastic configuration networks with maximum correntropy criterion for uncertain data regression. Inf. Sci. 473: 73-86 (2019) - [i9]Zheng Ma, Ming Li, Yu Guang Wang:
PAN: Path Integral Based Convolution for Deep Graph Neural Networks. CoRR abs/1904.10996 (2019) - [i8]Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang:
Fast Haar Transforms for Graph Neural Networks. CoRR abs/1907.04786 (2019) - [i7]Ming Li, Philip Broadbridge, Andriy Olenko, Yu Guang Wang:
Fast Tensor Needlet Transforms for Tangent Vector Fields on the Sphere. CoRR abs/1907.13339 (2019) - [i6]Quoc Thong Le Gia, Ming Li, Yu Guang Wang:
FaVeST: Fast Vector Spherical Harmonic Transforms. CoRR abs/1908.00041 (2019) - [i5]Yu Guang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan:
HaarPooling: Graph Pooling with Compressive Haar Basis. CoRR abs/1909.11580 (2019) - 2018
- [c1]Dianhui Wang, Ming Li:
Deep Stochastic Configuration Networks with Universal Approximation Property. IJCNN 2018: 1-8 - [i4]Ming Li, Dianhui Wang:
Two Dimensional Stochastic Configuration Networks for Image Data Analytics. CoRR abs/1809.02066 (2018) - 2017
- [j3]Ming Li, Dianhui Wang:
Insights into randomized algorithms for neural networks: Practical issues and common pitfalls. Inf. Sci. 382-383: 170-178 (2017) - [j2]Dianhui Wang, Ming Li:
Robust stochastic configuration networks with kernel density estimation for uncertain data regression. Inf. Sci. 412: 210-222 (2017) - [j1]Dianhui Wang, Ming Li:
Stochastic Configuration Networks: Fundamentals and Algorithms. IEEE Trans. Cybern. 47(10): 3466-3479 (2017) - [i3]Dianhui Wang, Ming Li:
Stochastic Configuration Networks: Fundamentals and Algorithms. CoRR abs/1702.03180 (2017) - [i2]Dianhui Wang, Ming Li:
Building Robust Stochastic Configuration Networks with Kernel Density Estimation. CoRR abs/1702.04459 (2017) - [i1]Dianhui Wang, Ming Li:
Deep Stochastic Configuration Networks: Universal Approximation and Learning Representation. CoRR abs/1702.05639 (2017)
Coauthor Index
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