Hong Zhu

Orcid: 0000-0003-0909-4894

Affiliations:
  • Shenzhen University, College of Computer Science and Software Engineering, Shenzhen, China
  • Macau University of Science and Technology, Faculty of Information Technology, Macau, China (PhD 2018)
  • Hebei University, College of Mathematics and Computer Science, Baoding, China (former)


According to our database1, Hong Zhu authored at least 13 papers between 2014 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2022
Fuzzy Monotonic K-Nearest Neighbor Versus Monotonic Fuzzy K-Nearest Neighbor.
IEEE Trans. Fuzzy Syst., 2022

2019
Multi-center convolutional descriptor aggregation for image retrieval.
Int. J. Mach. Learn. Cybern., 2019

Weight learning from cost matrix in weighted least squares model based on genetic algorithm.
Int. J. Bio Inspired Comput., 2019

2018
Training an extreme learning machine by localized generalization error model.
Soft Comput., 2018

Discovering the impact of hidden layer parameters on non-iterative training of feed-forward neural networks.
Soft Comput., 2018

2017
Monotonic classification extreme learning machine.
Neurocomputing, 2017

Discrete differential evolutions for the discounted {0-1} knapsack problem.
Int. J. Bio Inspired Comput., 2017

2016
An approach to sample selection from big data for classification.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016

2015
An Ordinal Random Forest and Its Parallel Implementation with MapReduce.
Proceedings of the 2015 IEEE International Conference on Systems, 2015

Research on ordinal regression of interval valued data.
Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, 2015

2014
Monotonic Decision Tree for Interval Valued Data.
Proceedings of the Machine Learning and Cybernetics, 2014

Parallel Ordinal Decision Tree Algorithm and Its Implementation in Framework of MapReduce.
Proceedings of the Machine Learning and Cybernetics, 2014

An Improved Approach to Ordinal Classification.
Proceedings of the Machine Learning and Cybernetics, 2014


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