Yu-Lin He

59 papers B 5C 2Misc 4Journal 40Unranked 8
YearRankTypeTitle / Venue / Authors
2026 J jnl
A data-driven fused kernel density estimator for multi-modal distribution.
Inf. Fusion
Yu-Lin He, Chun-Jia Chen, Jia-Qi Chen
2025 J jnl
A Novel Flexible Kernel Density Estimator for Multimodal Probability Density Functions.
CAAI Trans. Intell. Technol.
Jia-Qi Chen, Yu-Lin He, Yingchao Cheng, Philippe Fournier-Viger, Ponnuthurai Nagaratnam Suganthan, Joshua Zhexue Huang
2025 J jnl
A comprehensive multimodal benchmark of neuromorphic training frameworks for spiking neural networks.
Eng. Appl. Artif. Intell.
Yingchao Cheng, Wang-Xin Hu, Yu-Lin He, Joshua Zhexue Huang
2025 J jnl
A novel multi-source weighted naive Bayes classifier.
Inf. Sci.
Guiliang Ou, Yu-Lin He, Philippe Fournier-Viger, Joshua Zhexue Huang
2025 J jnl
Relaxed naïve Bayesian classifier based on maximum dependent attribute groups.
Inf. Sci.
Guiliang Ou, Yu-Lin He, Yingchao Cheng, Joshua Zhexue Huang
2024 J jnl
A multiple kernel-based kernel density estimator for multimodal probability density functions.
Eng. Appl. Artif. Intell.
Jia-Qi Chen, Yu-Lin He, Yingchao Cheng, Philippe Fournier-Viger, Joshua Zhexue Huang
2024 J jnl
A novel and efficient risk minimisation-based missing value imputation algorithm.
Knowl. Based Syst.
Yu-Lin He, Jia-Yin Yu, Xu Li, Philippe Fournier-Viger, Joshua Zhexue Huang
2024 J jnl
Introduction to the special issue on recent advances on digital economy-oriented artificial intelligence.
Eng. Appl. Artif. Intell.
Yu-Lin He, Philippe Fournier-Viger, Sebastián Ventura, Ling Zhang
2023 J jnl
Random vector functional link network with subspace-based local connections.
Appl. Intell.
Yu-Lin He, Zhen-Hao Yuan, Joshua Zhexue Huang
2022 J jnl
A novel dependency-oriented mixed-attribute data classification method.
Expert Syst. Appl.
Yu-Lin He, Guiliang Ou, Philippe Fournier-Viger, Joshua Zhexue Huang, Ponnuthurai Nagaratnam Suganthan
2022 J jnl
Creating synthetic minority class samples based on autoencoder extreme learning machine.
Pattern Recognit.
Yu-Lin He, Shengsheng Xu, Joshua Zhexue Huang
2021 J jnl
Novel kernel density estimator based on ensemble unbiased cross-validation.
Inf. Sci.
Yu-Lin He, Xuan Ye, De-Fa Huang, Joshua Zhexue Huang, Jun-Hai Zhai
2020 J jnl
A new approach to solve opinion dynamics on complex networks.
Expert Syst. Appl.
Wenting Wang, Yu-Lin He, Joshua Zhexue Huang, Liheng Ma
2020 J jnl
An Incremental Kernel Density Estimator for Data Stream Computation.
Complex.
Yu-Lin He, Jie Jiang, De-Xin Dai, Klohoun Fabrice
2020 J jnl
Novel electricity pattern identification system based on improved I-nice algorithm.
Comput. Ind. Eng.
Yu-Lin He, Honglian Qin, Joshua Zhexue Huang, Yi Jin
2019 J jnl
A new kernel density estimator based on the minimum entropy of data set.
Inf. Sci.
Jie Jiang, Yu-Lin He, De-Xin Dai, Joshua Zhexue Huang
2018 B conf
A Two-Stage Data Processing Algorithm to Generate Random Sample Partitions for Big Data Analysis.
CLOUD
Chenghao Wei, Salman Salloum, Tamer Z. Emara, Xiaoliang Zhang, Joshua Zhexue Huang, Yu-Lin He
2018 J jnl
Determining the optimal temperature parameter for Softmax function in reinforcement learning.
Appl. Soft Comput.
Yu-Lin He, Xiaoliang Zhang, Wei Ao, Joshua Zhexue Huang
2018 J jnl
Further improvements on extreme learning machine for interval neural network.
Neural Comput. Appl.
Li-fen Yang, Chong Liu, Hao Long, Rana Aamir Raza Ashfaq, Yu-Lin He
2018 — conf
Particle Swarm Optimization-Based Weighted-Nadaraya-Watson Estimator.
PAKDD (Workshops)
Jie Jiang, Yu-Lin He, Joshua Zhexue Huang
2018 J jnl
Random weight network-based fuzzy nonlinear regression for trapezoidal fuzzy number data.
Appl. Soft Comput.
Yu-Lin He, Chenghao Wei, Hao Long, Rana Aamir Raza Ashfaq, Joshua Zhexue Huang
2017 J jnl
A Random Sample Partition Data Model for Big Data Analysis.
CoRR
Salman Salloum, Yu-Lin He, Joshua Zhexue Huang, Xiaoliang Zhang, Tamer Z. Emara
2017 J jnl
Comments on "Local coupled extreme learning machine".
Neural Comput. Appl.
Wan-Guo Yu, Xu Zhou, Yu-Lin He, Rana Aamir Raza Ashfaq
2017 J jnl
Extreme learning machine with fuzzy input and fuzzy output for fuzzy regression.
Neural Comput. Appl.
Hai-Tao Liu, Jing Wang, Yu-Lin He, Rana Aamir Raza Ashfaq
2017 J jnl
Fuzziness based semi-supervised learning approach for intrusion detection system.
Inf. Sci.
Rana Aamir Raza Ashfaq, Xi-Zhao Wang, Joshua Zhexue Huang, Haider Abbas, Yu-Lin He
2017 — conf
I-Sampling: A New Block-Based Sampling Method for Large-Scale Dataset.
BigData Congress
Yu-Lin He, Joshua Zhexue Huang, Hao Long, Qiang Wang, Chenghao Wei
2017 — conf
Improving Generalization Capability of Extreme Learning Machine with Synthetic Instances Generation.
ICONIP (1)
Wei Ao, Yu-Lin He, Joshua Zhexue Huang, Yupeng He
2017 — conf
Self-adaptive Weighted Extreme Learning Machine for Imbalanced Classification Problems.
PAKDD (Workshops)
Hao Long, Yu-Lin He, Joshua Zhexue Huang, Qiang Wang
2017 J jnl
Toward an efficient fuzziness based instance selection methodology for intrusion detection system.
Int. J. Mach. Learn. Cybern.
Rana Aamir Raza Ashfaq, Yu-Lin He, De-gang Chen
2016 J jnl
An Improved Local Coupled Extreme Learning Machine.
J. Softw.
Chong Liu, Bing-Qiang Wang, Xiao-Lan Wang, Yu-Lin He, Rana Aamir Raza Ashfaq
2016 B conf
An approach to sample selection from big data for classification.
SMC
Sheng Xing, Yu-Lin He, Hong Zhu, Xizhao Wang
2016 C conf
Empirical analysis of asymptotic ensemble learning for big data.
BDCAT
Salman Salloum, Joshua Zhexue Huang, Yu-Lin He
2016 J jnl
Exact and approximate algorithms for discounted {0-1} knapsack problem.
Inf. Sci.
Yi-Chao He, Xi-Zhao Wang, Yu-Lin He, Shuliang Zhao, Wen-Bin Li
2016 J jnl
Fuzzy nonlinear regression analysis using a random weight network.
Inf. Sci.
Yu-Lin He, Xizhao Wang, Joshua Zhexue Huang
2016 — conf
Imbalanced ELM Based on Normal Density Estimation for Binary-Class Classification.
PAKDD Workshops
Yu-Lin He, Rana Aamir Raza Ashfaq, Joshua Zhexue Huang, Xizhao Wang
2016 J jnl
Impact of Variances of Random Weights and Biases on Extreme Learning Machine.
J. Softw.
Xiao Tao, Xu Zhou, Yu-Lin He, Rana Aamir Raza Ashfaq
2015 J jnl
Learning ELM-Tree from big data based on uncertainty reduction.
Fuzzy Sets Syst.
Ran Wang, Yu-Lin He, Chi-Yin Chow, Fang-Fang Ou, Jian Zhang
2015 J jnl
OWA operator based link prediction ensemble for social network.
Expert Syst. Appl.
Yu-Lin He, James Nga-Kwok Liu, Yan-Xing Hu, Xi-Zhao Wang
2015 — conf
Use Correlation Coefficients in Gaussian Process to Train Stable ELM Models.
PAKDD (1)
Yu-Lin He, Joshua Zhexue Huang, Xizhao Wang, Rana Aamir Raza
2014 — conf
A Further Investigation on the Reliability of Extreme Learning Machines.
ICDM Workshops
Yan-Xing Hu, Yuan Wang, Jane Jia You, James N. K. Liu, Yu-Lin He
2014 Misc conf
A hybrid algorithm for recommendation twitter peers.
SAC
James N. K. Liu, Zongnong Meng, Yan-Xing Hu, Yu-Lin He, Simon C. K. Shiu, Vincent W. S. Cho
2014 J jnl
A set covering based approach to find the reduct of variable precision rough set.
Inf. Sci.
James N. K. Liu, Yan-Xing Hu, Yu-Lin He
2014 J jnl
A study on relationships between heuristics and optimal cuts in decision tree induction.
Comput. Electr. Eng.
Hong-Yan Ji, Xi-Zhao Wang, Yu-Lin He, Wen-Liang Li
2014 J jnl
A study on residence error of training an extreme learning machine and its application to evolutionary algorithms.
Neurocomputing
Ai-Min Fu, Xi-Zhao Wang, Yu-Lin He, Lai-Sheng Wang
2014 B conf
An advancing investigation on reduct and consistency for decision tables in Variable Precision Rough Set models.
FUZZ-IEEE
James N. K. Liu, Jane Jia You, Yan-Xing Hu, Yu-Lin He
2014 J jnl
Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis.
Inf. Sci.
Yu-Lin He, Ran Wang, Sam Kwong, Xi-Zhao Wang
2014 J jnl
Domain ontology graph model and its application in Chinese text classification.
Neural Comput. Appl.
James N. K. Liu, Yu-Lin He, Edward H. Y. Lim, Xizhao Wang
2014 C conf
Integrating Local Information-based Link Prediction Algorithms with OWA Operator.
ICPRAM
James N. K. Liu, Yu-Lin He, Yan-Xing Hu, Xi-Zhao Wang, Simon C. K. Shiu
2014 J jnl
Non-Naive Bayesian Classifiers for Classification Problems With Continuous Attributes.
IEEE Trans. Cybern.
Xi-Zhao Wang, Yu-Lin He, Debby Dan Wang
2014 B conf
Regression ensemble with PSO algorithms based fuzzy integral.
IEEE Congress on Evolutionary Computation
James Nga-Kwok Liu, Yan-Xing Hu, Yu-Lin He, Xizhao Wang
2013 J jnl
A Combined Position Evaluation Function in Chinese Chess Computer Game.
Trans. Comput. Sci.
Yu-Lin He, Xizhao Wang, Tingting Fu
2013 J jnl
A New Method for Knowledge and Information Management Domain Ontology Graph Model.
IEEE Trans. Syst. Man Cybern. Syst.
James N. K. Liu, Yu-Lin He, Edward H. Y. Lim, Xizhao Wang
2013 Misc conf
Comparison of geometric and arithmetic means for bandwidth selection in Nadaraya-Watson kernel regression estimator.
ICMLC
Li-Yuan Xu, Min Zhang, Wei Zhu, Yu-Lin He
2012 B conf
Improving kernel incapability by equivalent probability in flexible naïve Bayesian.
FUZZ-IEEE
James N. K. Liu, Yu-Lin He, Xizhao Wang
2012 — conf
Naive Bayesian Classifier Based on Neighborhood Probability.
IPMU (3)
James N. K. Liu, Yu-Lin He, Xizhao Wang, Yan-Xing Hu
2012 J jnl
Optimal bandwidth selection for re-substitution entropy estimation.
Appl. Math. Comput.
Yu-Lin He, James N. K. Liu, Xizhao Wang, Yan-Xing Hu
2011 Misc conf
A comparative study among different kernel functions in flexible naïve Bayesian classification.
ICMLC
James N. K. Liu, Yu-Lin He, Xizhao Wang, Yan-Xing Hu
2011 J jnl
Particle swarm optimization for determining fuzzy measures from data.
Inf. Sci.
Xizhao Wang, Yu-Lin He, Ling-Cai Dong, Huanyu Zhao
2010 Misc conf
A new instance selection algorithm based on contribution for nearest neighbour classification.
ICMLC
Yong-Hua Cai, Bo Wu, Yu-Lin He, Ye Zhang