Ming Li

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 65

Top Topics

Student Engagement

Graph Representation

Density Estimation

Top Venues

Knowl. Based Syst.

Neural Networks

Publications

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) (2024)
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) (2024)
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) (2024)
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 (2024)
Ming Li, Alessio Micheli, Yu Guang Wang, Shirui Pan, Pietro Lió, Giorgio Stefano Gnecco, Marcello Sanguineti
Guest Editorial: Deep Neural Networks for Graphs: Theory, Models, Algorithms, and Applications. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Zhehan Zhao, Lu Bai, Lixin Cui, Ming Li, Yue Wang, Lixiang Xu, Edwin R. Hancock
ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks. CoRR (2024)
Lifan Jiang, Zhihui Wang, Changmiao Wang, Ming Li, Jiaxu Leng, Xindong Wu
ConsistencyDet: A Robust Object Detector with a Denoising Paradigm of Consistency Model. CoRR (2024)
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) (2024)
Yizhen Zheng, Ming Jin, Shirui Pan, Yuan-Fang Li, Hao Peng, Ming Li, Zhao Li
Toward Graph Self-Supervised Learning With Contrastive Adjusted Zooming. IEEE Trans. Neural Networks Learn. Syst. 35 (7) (2024)
Guangrui Yang, Jianfei Li, Ming Li, Han Feng, Ding-Xuan Zhou
Bridging Smoothness and Approximation: Theoretical Insights into Over-Smoothing in Graph Neural Networks. CoRR (2024)
Yu-Ting Chen, Ming Li, Mutlu Cukurova
Unleashing imagination: an effective pedagogical approach to integrate into spherical video-based virtual reality to improve students' creative writing. Educ. Inf. Technol. 29 (6) (2024)
Ming Li, Siwei Zhou, Yuting Chen, Changqin Huang, Yunliang Jiang
EduCross: Dual adversarial bipartite hypergraph learning for cross-modal retrieval in multimodal educational slides. Inf. Fusion 109 (2024)
Mingyue Niu, Ming Li, Changzeng Fu
PointTransform Networks for automatic depression level prediction via facial keypoints. Knowl. Based Syst. 297 (2024)
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 (2024)
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)
Yi Wang, Changqin Huang, Ming Li, Qionghao Huang, Xuemei Wu, Jia Wu
AG-Meta: Adaptive graph meta-learning via representation consistency over local subgraphs. Pattern Recognit. 151 (2024)
Zhuo Xu, Lu Bai, Lixin Cui, Ming Li, Yue Wang, Edwin R. Hancock
HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning. CoRR (2024)
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 (2024)
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 (2023)
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) (2023)
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 (2023)
Xinhong Meng, Meng Hu, Hailiang Ye, Ming Li, Feilong Cao
A Global-and-Local Feature Fusion Network for Point Cloud Classification. ICMLC (2023)
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 (2023)
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) (2023)
Ming Li, Yu-Ting 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 (2023)
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 (2023)
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 (2023)
Yangjie Qin, Ming Li, Jia Zhu
Privacy-preserving federated learning framework in multimedia courses recommendation. Wirel. Networks 29 (4) (2023)
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) (2023)
Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao
Embedding Graphs on Grassmann Manifold. CoRR (2022)
Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao
Embedding graphs on Grassmann manifold. Neural Networks 152 (2022)
Yu-Ting 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) (2022)
Yuzhi Song, Hailiang Ye, Ming Li, Feilong Cao
Deep multi-graph neural networks with attention fusion for recommendation. Expert Syst. Appl. 191 (2022)
Kaixuan Yao, Jiye Liang, Jianqing Liang, Ming Li, Feilong Cao
Multi-view graph convolutional networks with attention mechanism. Artif. Intell. 307 (2022)
Ming Li, Giorgio Gnecco, Marcello Sanguineti
Deeper Insights into Neural Nets with Random Weights. AI (2022)
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) (2022)
Quoc Thong Le Gia, Ming Li, Yu Guang Wang
Algorithm 1018: FaVeST - Fast Vector Spherical Harmonic Transforms. ACM Trans. Math. Softw. 47 (4) (2021)
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montúfar
How Framelets Enhance Graph Neural Networks. ICML (2021)
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Liò, Ming Li, Guido Montúfar
How Framelets Enhance Graph Neural Networks. CoRR (2021)
Changqin Huang, Ming Li, Dianhui Wang
Stochastic configuration network ensembles with selective base models. Neural Networks 137 (2021)
Ming Li, Dianhui Wang
2-D Stochastic Configuration Networks for Image Data Analytics. IEEE Trans. Cybern. 51 (1) (2021)
Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Liò
Path Integral Based Convolution and Pooling for Graph Neural Networks. NeurIPS (2020)
Sho Sonoda, Ming Li, Feilong Cao, Changqin Huang, Yu Guang Wang
On the Approximation Lower Bound for Neural Nets with Random Weights. CoRR (2020)
Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang
Fast Haar Transforms for Graph Neural Networks. Neural Networks 128 (2020)
Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Lió
Path Integral Based Convolution and Pooling for Graph Neural Networks. CoRR (2020)
Daniel Vidali Fryer, Ming Li, Andriy Olenko
rcosmo: R Package for Analysis of Spherical, HEALPix and Cosmological Data. R J. 12 (1) (2020)
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 (2020)
Yuguang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan
Haar Graph Pooling. ICML (2020)
Zhengyang Wu, Ming Li, Yong Tang, Qingyu Liang
Exercise recommendation based on knowledge concept prediction. Knowl. Based Syst. 210 (2020)
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 (2020)
Ming Li, Changqin Huang, Dianhui Wang
Robust stochastic configuration networks with maximum correntropy criterion for uncertain data regression. Inf. Sci. 473 (2019)
Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang
Fast Haar Transforms for Graph Neural Networks. CoRR (2019)
Yu Guang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan
HaarPooling: Graph Pooling with Compressive Haar Basis. CoRR (2019)
Quoc Thong Le Gia, Ming Li, Yu Guang Wang
FaVeST: Fast Vector Spherical Harmonic Transforms. CoRR (2019)
Zheng Ma, Ming Li, Yu Guang Wang
PAN: Path Integral Based Convolution for Deep Graph Neural Networks. CoRR (2019)
Ming Li, Philip Broadbridge, Andriy Olenko, Yu Guang Wang
Fast Tensor Needlet Transforms for Tangent Vector Fields on the Sphere. CoRR (2019)
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) (2019)
Dianhui Wang, Ming Li
Deep Stochastic Configuration Networks with Universal Approximation Property. IJCNN (2018)
Ming Li, Dianhui Wang
Two Dimensional Stochastic Configuration Networks for Image Data Analytics. CoRR (2018)
Ming Li, Dianhui Wang
Insights into randomized algorithms for neural networks: Practical issues and common pitfalls. Inf. Sci. (2017)
Dianhui Wang, Ming Li
Building Robust Stochastic Configuration Networks with Kernel Density Estimation. CoRR (2017)
Dianhui Wang, Ming Li
Stochastic Configuration Networks: Fundamentals and Algorithms. CoRR (2017)
Dianhui Wang, Ming Li
Deep Stochastic Configuration Networks: Universal Approximation and Learning Representation. CoRR (2017)
Dianhui Wang, Ming Li
Stochastic Configuration Networks: Fundamentals and Algorithms. IEEE Trans. Cybern. 47 (10) (2017)
Dianhui Wang, Ming Li
Robust stochastic configuration networks with kernel density estimation for uncertain data regression. Inf. Sci. 412 (2017)