Jie Yang

Orcid: 0000-0003-1318-3996

Affiliations:

Dalian University of Technology, School of Mathematical Sciences, China (PhD)

According to our database¹, Jie Yang authored at least 35 papers between 2004 and 2024.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

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Bibliography

2024

A New Oversampling Method Based on Triangulation of Sample Space.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Syst., February, 2024

Zero-order fuzzy neural network with adaptive fuzzy partition and its applications on high-dimensional problems.

[BibT_eX]

[DOI]

Neurocomputing, February, 2024

2023

Coding Method Based on Fuzzy C-Means Clustering for Spiking Neural Network With Triangular Spike Response Function.

[BibT_eX]

[DOI]

IEEE Trans. Fuzzy Syst., December, 2023

A new boundary-degree-based oversampling method for imbalanced data.

[BibT_eX]

[DOI]

Yueqi Chen

Witold Pedrycz

Jie Yang

Appl. Intell., November, 2023

A novel parallel merge neural network with streams of spiking neural network and artificial neural network.

[BibT_eX]

[DOI]

Jie Yang

Junhong Zhao

Inf. Sci., 2023

Oversampling method based on GAN for tabular binary classification problems.

[BibT_eX]

[DOI]

Intell. Data Anal., 2023

2022

Spiking Neural Network Regularization With Fixed and Adaptive Drop-Keep Probabilities.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2022

A New Fuzzy Spiking Neural Network Based on Neuronal Contribution Degree.

[BibT_eX]

[DOI]

IEEE Trans. Fuzzy Syst., 2022

A new classifier for imbalanced data with iterative learning process and ensemble operating process.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2022

2021

A New Oversampling Method Based on the Classification Contribution Degree.

[BibT_eX]

[DOI]

Symmetry, 2021

2020

Binary Output Layer of Extreme Learning Machine for Solving Multi-class Classification Problems.

[BibT_eX]

[DOI]

Neural Process. Lett., 2020

Learning imbalanced datasets based on SMOTE and Gaussian distribution.

[BibT_eX]

[DOI]

Inf. Sci., 2020

2019

A Genetic XK-Means Algorithm with Empty Cluster Reassignment.

[BibT_eX]

[DOI]

Symmetry, 2019

Extreme learning machine with local connections.

[BibT_eX]

[DOI]

Neurocomputing, 2019

Interpretability for Neural Networks from the Perspective of Probability Density.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

2018

A New Conjugate Gradient Method with Smoothing L<sub>1/2</sub> Regularization Based on a Modified Secant Equation for Training Neural Networks.

[BibT_eX]

[DOI]

Neural Process. Lett., 2018

The convergence analysis of SpikeProp algorithm with smoothing L1∕2 regularization.

[BibT_eX]

[DOI]

Neural Networks, 2018

Robustness of classification ability of spiking neural networks.

[BibT_eX]

[DOI]

Jie Yang

Pingping Zhang

Yan Liu

CoRR, 2018

2015

An Algorithm for Motif Discovery with Iteration on Lengths of Motifs.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2015

2014

Double parallel feedforward neural network based on extreme learning machine with L<sub>1/2</sub> regularizer.

[BibT_eX]

[DOI]

Atlas Khan

Jie Yang

Wei Wu

Neurocomputing, 2014

2013

Modified gradient-based learning for local coupled feedforward neural networks with Gaussian basis function.

[BibT_eX]

[DOI]

Neural Comput. Appl., 2013

2012

A Modified Spiking Neuron that Involves Derivative of the State Function at Firing Time.

[BibT_eX]

[DOI]

Wenyu Yang

Jie Yang

Wei Wu

Neural Process. Lett., 2012

Negative effects of sufficiently small initialweights on back-propagation neural networks.

[BibT_eX]

[DOI]

J. Zhejiang Univ. Sci. C, 2012

A remark on the error-backpropagation learning algorithm for spiking neural networks.

[BibT_eX]

[DOI]

Jie Yang

Wenyu Yang

Wei Wu

Appl. Math. Lett., 2012

A Modified One-Layer Spiking Neural Network Involves Derivative of the State Function at Firing Time.

[BibT_eX]

[DOI]

Wenyu Yang

Jie Yang

Wei Wu

Proceedings of the Advances in Neural Networks - ISNN 2012, 2012

2011

Binary Higher Order Neural Networks for Realizing Boolean Functions.

[BibT_eX]

[DOI]

Chao Zhang

Jie Yang

Wei Wu

IEEE Trans. Neural Networks, 2011

Convergence of Cyclic and Almost-Cyclic Learning With Momentum for Feedforward Neural Networks.

[BibT_eX]

[DOI]

Jian Wang

Jie Yang

Wei Wu

IEEE Trans. Neural Networks, 2011

2010

A modified gradient-based neuro-fuzzy learning algorithm and its convergence.

[BibT_eX]

[DOI]

Inf. Sci., 2010

Choice of initial bias in max-min fuzzy neural networks.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2010

2009

An intuitionistic fuzzy associative memory network and its learning rule.

[BibT_eX]

[DOI]

Proceedings of the 2009 IEEE International Conference on Granular Computing, 2009

An Attribute Value Reduction Algorithm Based on Set Operations.

[BibT_eX]

[DOI]

Proceedings of the First International Workshop on Database Technology and Applications, 2009

2007

Is bias dispensable for fuzzy neural networks?

[BibT_eX]

[DOI]

Jie Yang

Wei Wu

Fuzzy Sets Syst., 2007

Dispensability of Bias for Three-layer Max-min Fuzzy Neural Networks.

[BibT_eX]

[DOI]

Jie Yang

Long Li

Yan Liu

Proceedings of the Third International Conference on Natural Computation, 2007

2005

A New Training Algorithm for a Fuzzy Perceptron and Its Convergence.

[BibT_eX]

[DOI]

Jie Yang

Wei Wu

Zhiqiong Shao

Proceedings of the Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005

2004

Recent Developments on Convergence of Online Gradient Methods for Neural Network Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Networks, 2004

Jie Yang

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