Ming Li

Postdoc

Australian Mathematial Society Member

IEEE Member

South China Normal University

La Trobe University

I am Postdoctor Fellow at the School of Information Technology in Education, South China Normal University, Guangzhou, China, and a Research Officer at the Department of Mathematics and Statistics, within the School of Engineering and Mathematical Sciences (SEMS), College of Science, Health and Engineering (CSHE), La Trobe Univesity. I obtained my Ph.D.degree in computer science and IT from La Trobe University, Melbourne, Australia, in 2017. Before that, I received the bachelor’s degree in information and computing sciences from Shandong Normal University, Jinan, China, in 2010, and the master’s degree in applied mathematics from China Jiliang University, Hangzhou, China, in 2013.

Research Interests

Machine Learning and Data Analytics

Randomized Learning Algorithms for Neural Networks
Deep Neural Networks and Learning Representation
Robust Data Modelling

Applied and Computational Harmonic Analysis

Scattered Data Approximation

Education

PhD, Computer Science and IT, La Trobe University, Australia, Dec. 2013 – Sep. 2017

Topic: Randomized Algorithms for Neural Networks with Applications in Data Analytics

MSc, Applied Mathematics, China Jiliang University, China, Sep. 2010 – Jun. 2013

Topic: Scattered Data Approximation on the Sphere

BSc, Information and Computing Sciences, Shandong Normal University, China, Sep. 2006 – Jun. 2010

Publications

M. Li and D. Wang. Two dimensional stochastic configuration networks for image data analytics. submitted to IEEE Transactions on Cybernetics, arXiv:1809.02066, Sep. 2018. [Link]

M. Li, C. Huang, and D. Wang. Robust stochastic configuration networks with maximum correntropy criterion for uncertain data regression. Accepted in Information Sciences, 2018, available online. [Link]

D. Wang and M. Li. Deep stochastic configuration networks with universal approximation property. arXiv:1702.05639, to appear in IJCNN, 2018. [Link]

D. Wang and M. Li. Stochastic configuration networks: Fundamentals and algorithms. IEEE Transactions on Cybernetics, vol. 47, no.10, October, 2017.[Paper] [Code]

D. Wang and M. Li. Robust stochastic configuration networks with kernel density estimation for uncertain data regression. Information Sciences, vol. 412-413, pp. 210-222, 2017. [Paper] [Code]

M. Li and D. Wang. Insights into randomized algorithms for neural networks: Practical issues and common pitfalls. Information Sciences, vol. 382-383, pp. 170-178, 2017. [Paper]

F. Cao and M. Li. Spherical data fitting by multiscale moving least squares. Applied Mathematical Modelling, vol. 39, no. 12, pp. 3448-3458, 2015. [Paper]

Z. Chen, F. Cao, and M. Li. Scattered data quasi-interpolation on spheres. Mathematical Methods in the Applied Sciences, vol. 38, no. 12, pp. 2527-2536, 2015. [Paper]

M. Li and F. Cao. Multiscale interpolation on the sphere: Convergence rate and inverse theorem. Applied Mathematics and Computation, vol. 263, pp. 134-150, 2015. [Paper]

M. Li and F. Cao. Local uniform error estimates for spherical basis functions interpolation. Mathematical Methods in the Applied Sciences, vol. 37, no. 9, pp. 1364-1376, 2014. [Paper]

M. Li, F. Cao, and Z. Chen. The equivalent theorem for jackson-type operators on spherical cap. Journal of Computational Analysis and Applications, vol. 15, no. 4, pp. 778-787, 2013. [Paper]

C. Ding, M. Li, F. Cao. Pointwise error estimates for spherical hybrid interpolation. Journal of Computational Analysis and Applications, vol. 26, no. 1, pp. 77-84, Jan. 2019. [Paper]

C. Ding, M. Li, F. Cao. Lp approximation errors for hybrid interpolation on the unit sphere. Journal of Computational Analysis and Applications, vol. 27, no. 1, pp. 104-117, July 2019. [Paper]

Professional Activities (Regular Reviewer)

IEEE Transactions on Neural Networks and Learning Systems

IEEE Transactions on Cybernetics (Outstanding Reviewer in 2016 and 2017)

Information Sciences

Neurocomputing

Applied Mathematical Modelling

Applied Soft Computing

WIREs Data Mining and Knowledge Discovery

International Journal of Machine Learning and Cybernetics

International Journal of Machine Intelligence and Sensory Signal Processing

Research Interests

Education

Publications

Professional Activities (Regular Reviewer)

Curriculum vitae