Ming Li

Orcid: 0000-0002-1218-2804

Affiliations:

Zhejiang Normal University, Department of Computer Science, Jinhua, China
South China Normal University, School of Information Technology in Education, Guangzhou, China
La Trobe University, Department of Computer Science and Information Technology, Melbourne, VIC , Australia (PhD)

According to our database¹, Ming Li authored at least 61 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Multimodal graph learning based on 3D Haar semi-tight framelet for student engagement prediction.

[BibT_eX]

[DOI]

Inf. Fusion, May, 2024

A Simple Yet Effective Framelet-Based Graph Neural Network for Directed Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Artif. Intell., April, 2024

Incorporation of peer-feedback into the pedagogical use of spherical video-based virtual reality in writing education.

[BibT_eX]

[DOI]

Br. J. Educ. Technol., March, 2024

Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., February, 2024

A joint parcellation and boundary network with multi-rate-shared dilated graph attention for cortical surface parcellation.

[BibT_eX]

[DOI]

Medical Biol. Eng. Comput., February, 2024

QBER: Quantum-based Entropic Representations for un-attributed graphs.

[BibT_eX]

[DOI]

Pattern Recognit., January, 2024

A Systematic Review of Research on Immersive Technology-Enhanced Writing Education: The Current State and a Research Agenda.

[BibT_eX]

[DOI]

IEEE Trans. Learn. Technol., 2024

Real-time E-bike Route Planning with Battery Range Prediction.

[BibT_eX]

[DOI]

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

BLoG: Bootstrapped graph representation learning with local and global regularization for recommendation.

[BibT_eX]

[DOI]

Pattern Recognit., December, 2023

Triplet teaching graph contrastive networks with self-evolving adaptive augmentation.

[BibT_eX]

[DOI]

Pattern Recognit., October, 2023

A new deep graph attention approach with influence and preference relationship reconstruction for rate prediction recommendation.

[BibT_eX]

[DOI]

Inf. Process. Manag., September, 2023

From motivational experience to creative writing: A motivational AR-based learning approach to promoting Chinese writing performance and positive writing behaviours.

[BibT_eX]

[DOI]

Comput. Educ., September, 2023

Multiple Pedestrian Tracking With Graph Attention Map on Urban Road Scene.

[BibT_eX]

[DOI]

IEEE Trans. Intell. Transp. Syst., August, 2023

Privacy-preserving federated learning framework in multimedia courses recommendation.

[BibT_eX]

[DOI]

Yangjie Qin

Ming Li

Jia Zhu

Wirel. Networks, May, 2023

Are Graph Convolutional Networks With Random Weights Feasible?

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

GoLoG: Global-to-Local Decoupling Graph Network With Joint Optimization for Hyperspectral Image Classification.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2023

Revisiting graph neural networks from hybrid regularized graph signal reconstruction.

[BibT_eX]

[DOI]

Neural Networks, 2023

MathNet: Haar-like wavelet multiresolution analysis for graph representation learning.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2023

A disentangled linguistic graph model for explainable aspect-based sentiment analysis.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2023

TeFNA: Text-centered fusion network with crossmodal attention for multimodal sentiment analysis.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2023

Permutation Equivariant Graph Framelets for Heterophilous Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2023

AERK: Aligned Entropic Reproducing Kernels through Continuous-time Quantum Walks.

[BibT_eX]

[DOI]

CoRR, 2023

Stability and Generalization of lp-Regularized Stochastic Learning for GCN.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

A Global-and-Local Feature Fusion Network for Point Cloud Classification.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Cybernetics, 2023

How Powerful are Shallow Neural Networks with Bandlimited Random Weights?

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

Empowering IoT Predictive Maintenance Solutions With AI: A Distributed System for Manufacturing Plant-Wide Monitoring.

[BibT_eX]

[DOI]

IEEE Trans. Ind. Informatics, 2022

Embedding graphs on Grassmann manifold.

[BibT_eX]

[DOI]

Neural Networks, 2022

Deep multi-graph neural networks with attention fusion for recommendation.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2022

HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification.

[BibT_eX]

[DOI]

CoRR, 2022

Promoting deep writing with immersive technologies: An SVVR-supported Chinese composition writing approach for primary schools.

[BibT_eX]

[DOI]

Br. J. Educ. Technol., 2022

Multi-view graph convolutional networks with attention mechanism.

[BibT_eX]

[DOI]

Artif. Intell., 2022

Neural Network Model Reconstructed from Entangled Quantum States.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Feedforward Neural Network Reconstructed from High-order Quantum Systems.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Deeper Insights into Neural Nets with Random Weights.

[BibT_eX]

[DOI]

Ming Li

Giorgio Gnecco

Marcello Sanguineti

Proceedings of the AI 2021: Advances in Artificial Intelligence, 2022

2021

Algorithm 1018: FaVeST - Fast Vector Spherical Harmonic Transforms.

[BibT_eX]

[DOI]

Quoc Thong Le Gia

Ming Li

Yu Guang Wang

ACM Trans. Math. Softw., 2021

2-D Stochastic Configuration Networks for Image Data Analytics.

[BibT_eX]

[DOI]

Ming Li

Dianhui Wang

IEEE Trans. Cybern., 2021

Stochastic configuration network ensembles with selective base models.

[BibT_eX]

[DOI]

Changqin Huang

Ming Li

Dianhui Wang

Neural Networks, 2021

Effective multiple pedestrian tracking system in video surveillance with monocular stationary camera.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2021

Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming.

[BibT_eX]

[DOI]

CoRR, 2021

How Framelets Enhance Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Social participation of the elderly in China: The roles of conventional media, digital access and social media engagement.

[BibT_eX]

[DOI]

Telematics Informatics, 2020

rcosmo: R Package for Analysis of Spherical, HEALPix and Cosmological Data.

[BibT_eX]

[DOI]

Daniel Vidali Fryer

Ming Li

Andriy Olenko

R J., 2020

Fast Haar Transforms for Graph Neural Networks.

[BibT_eX]

[DOI]

Neural Networks, 2020

Exercise recommendation based on knowledge concept prediction.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2020

On the Approximation Lower Bound for Neural Nets with Random Weights.

[BibT_eX]

[DOI]

CoRR, 2020

Graph Neural Networks with Haar Transform-Based Convolution and Pooling: A Complete Guide.

[BibT_eX]

[DOI]

CoRR, 2020

Path Integral Based Convolution and Pooling for Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Haar Graph Pooling.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Robust stochastic configuration networks with maximum correntropy criterion for uncertain data regression.

[BibT_eX]

[DOI]

Ming Li

Changqin Huang

Dianhui Wang

Inf. Sci., 2019

HaarPooling: Graph Pooling with Compressive Haar Basis.

[BibT_eX]

[DOI]

CoRR, 2019

FaVeST: Fast Vector Spherical Harmonic Transforms.

[BibT_eX]

[DOI]

Quoc Thong Le Gia

Ming Li

Yu Guang Wang

CoRR, 2019

Fast Tensor Needlet Transforms for Tangent Vector Fields on the Sphere.

[BibT_eX]

[DOI]

CoRR, 2019

PAN: Path Integral Based Convolution for Deep Graph Neural Networks.

[BibT_eX]

[DOI]

Zheng Ma

Ming Li

Yu Guang Wang

CoRR, 2019

Improved randomized learning algorithms for imbalanced and noisy educational data classification.

[BibT_eX]

[DOI]

Computing, 2019

2018

Two Dimensional Stochastic Configuration Networks for Image Data Analytics.

[BibT_eX]

[DOI]

Ming Li

Dianhui Wang

CoRR, 2018

Deep Stochastic Configuration Networks with Universal Approximation Property.

[BibT_eX]

[DOI]

Dianhui Wang

Ming Li

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017

Stochastic Configuration Networks: Fundamentals and Algorithms.

[BibT_eX]

[DOI]

Dianhui Wang

Ming Li

IEEE Trans. Cybern., 2017

Robust stochastic configuration networks with kernel density estimation for uncertain data regression.

[BibT_eX]

[DOI]

Dianhui Wang

Ming Li

Inf. Sci., 2017

Insights into randomized algorithms for neural networks: Practical issues and common pitfalls.

[BibT_eX]

[DOI]

Ming Li

Dianhui Wang

Inf. Sci., 2017

Deep Stochastic Configuration Networks: Universal Approximation and Learning Representation.

[BibT_eX]

[DOI]

Dianhui Wang

Ming Li

CoRR, 2017

Building Robust Stochastic Configuration Networks with Kernel Density Estimation.

[BibT_eX]

[DOI]

Dianhui Wang

Ming Li

CoRR, 2017

Ming Li

Timeline

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