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Journal Articles
- 2024
[j19]Hong-Jie Xing, Wei-Tao Liu, Xi-Zhao Wang:
Bounded exponential loss function based AdaBoost ensemble of OCSVMs. Pattern Recognit. 148: 110191 (2024)- [j18]Hong-Jie Xing, Hui-Nan Wu, Ping-Ping Zhang:
Deep multi-sphere support vector data description based on disentangled representation learning. Pattern Recognit. 156: 110842 (2024) - 2023
- [j17]Hong-Jie Xing, Ping-Ping Zhang:
Contrastive deep support vector data description. Pattern Recognit. 143: 109820 (2023) - 2022
- [j16]Hong-Jie Xing, Zi-Chuan He
:
Adaptive loss function based least squares one-class support vector machine. Pattern Recognit. Lett. 156: 174-182 (2022) - 2021
- [j15]Hong-Jie Xing, Ya-Jie Liu, Zi-Chuan He:
Robust sparse coding for one-class classification based on correntropy and logarithmic penalty function. Pattern Recognit. 111: 107685 (2021) - 2020
- [j14]Hong-Jie Xing, Wei-Tao Liu:
Robust AdaBoost based ensemble of one-class support vector machines. Inf. Fusion 55: 45-58 (2020) - [j13]Hong-Jie Xing, Li-Fei Li:
Robust least squares one-class support vector machine. Pattern Recognit. Lett. 138: 571-578 (2020) - 2018
- [j12]Hong-Jie Xing, Man Ji:
Robust one-class support vector machine with rescaled hinge loss function. Pattern Recognit. 84: 152-164 (2018) - 2017
- [j11]Hong-Jie Xing, Xi-Zhao Wang:
Selective ensemble of SVDDs with Renyi entropy based diversity measure. Pattern Recognit. 61: 185-196 (2017) - 2016
- [j10]Bao-Gang Hu, Hong-Jie Xing:
An Optimization Approach of Deriving Bounds between Entropy and Error from Joint Distribution: Case Study for Binary Classifications. Entropy 18(2): 59 (2016) - 2015
- [j9]Xizhao Wang, Hong-Jie Xing, Yan Li, Qiang Hua, Chun-Ru Dong, Witold Pedrycz:
A Study on Relationship Between Generalization Abilities and Fuzziness of Base Classifiers in Ensemble Learning. IEEE Trans. Fuzzy Syst. 23(5): 1638-1654 (2015) - 2014
- [j8]Hong-Jie Xing, Huan-Ru Ren:
Regularized correntropy criterion based feature extraction for novelty detection. Neurocomputing 133: 483-490 (2014) - [j7]Hong-Jie Xing, Minghu Ha:
Further improvements in Feature-Weighted Fuzzy C-Means. Inf. Sci. 267: 1-15 (2014) - 2013
- [j6]Hong-Jie Xing, Xin-Mei Wang:
Training extreme learning machine via regularized correntropy criterion. Neural Comput. Appl. 23(7-8): 1977-1986 (2013) - 2011
- [j5]Hong Zhang, Minghu Ha, Hong-Jie Xing:
Chance-constrained programming on sugeno measure space. Expert Syst. Appl. 38(9): 11527-11533 (2011) - [j4]Hao-Xin Zhao, Hong-Jie Xing, Xi-Zhao Wang:
Two-stage dimensionality reduction approach based on 2DLDA and fuzzy rough sets technique. Neurocomputing 74(17): 3722-3727 (2011) - 2009
- [j3]Minghu Ha, Hong Zhang, Witold Pedrycz, Hong-Jie Xing:
The expected value models on Sugeno measure space. Int. J. Approx. Reason. 50(7): 1022-1035 (2009) - [j2]Hong-Jie Xing, Bao-Gang Hu:
Two-Phase Construction of Multilayer Perceptrons Using Information Theory. IEEE Trans. Neural Networks 20(4): 715-721 (2009) - 2008
- [j1]Hong-Jie Xing, Bao-Gang Hu:
An adaptive fuzzy c-means clustering-based mixtures of experts model for unlabeled data classification. Neurocomputing 71(4-6): 1008-1021 (2008)
Conference and Workshop Papers
- 2018
- [c13]Wei-Tao Liu, Hong-Jie Xing:
Rotation Based Ensemble of One-Class Support Vector Machines. ICMLC 2018: 178-183 - 2016
- [c12]Qing-Zhen Shang, Hong-Jie Xing:
Correntropy based self-organizing map. ICMLC 2016: 369-374 - 2014
- [c11]Yan Li, Hong-Jie Xing, Qiang Hua, Xi-Zhao Wang, Prerna Batta, Soroush Haeri, Ljiljana Trajkovic:
Classification of BGP anomalies using decision trees and fuzzy rough sets. SMC 2014: 1312-1317 - 2012
- [c10]Hong-Jie Xing, Jian-Guo Wu, Xue-Fang Chen:
Modified AdaBoost based OCSVM ensemble for image retrieval. ICMLC 2012: 1048-1053 - [c9]Hong-Jie Xing, Xue-Fang Chen:
Selective Ensemble of Support Vector Data Descriptions for Novelty Detection. ISNN (1) 2012: 468-477 - [c8]Huan-Ru Ren, Hong-Jie Xing:
Robust feature extraction for novelty detection based on regularized correntropy criterion. SMC 2012: 975-980 - 2011
- [c7]Hong-Jie Xing, Xizhao Wang, Minghu Ha:
A comparative experimental study of feature-weight learning approaches. SMC 2011: 3500-3505 - [c6]Xue-Fang Chen, Hong-Jie Xing, Xi-Zhao Wang:
A modified AdaBoost method for one-class SVM and its application to novelty detection. SMC 2011: 3506-3511 - 2008
- [c5]Hong-Jie Xing, Minghu Ha, Da-Zeng Tian, Bao-Gang Hu:
A novel support vector machine with its features weighted by mutual information. IJCNN 2008: 315-320 - [c4]Hong-Jie Xing, Xizhao Wang, Ruixian Zhu, Dan Wang:
Application of kernel learning vector quantization to novelty detection. SMC 2008: 439-443 - 2006
- [c3]Yong Wang, Hong-Jie Xing:
Knowledge Discovery and Integration Based on A Novel Neural Network Ensemble Model. SKG 2006: 9 - 2005
- [c2]Hong-Jie Xing, Yujiu Yang, Yong Wang, Bao-Gang Hu:
Sparse Kernel Fisher Discriminant Analysis. ISNN (1) 2005: 824-830 - 2004
- [c1]Bao-Gang Hu, Hong-Jie Xing, Yujiu Yang:
Geometric Interpretation of Nonlinear Approximation Capability for Feedforward Neural Networks. ISNN (1) 2004: 7-13
Informal and Other Publications
- 2013
- [i2]Bao-Gang Hu, Hong-Jie Xing:
A New Approach of Deriving Bounds between Entropy and Error from Joint Distribution: Case Study for Binary Classifications. CoRR abs/1303.0943 (2013) - 2012
- [i1]Bao-Gang Hu, Hong-Jie Xing:
Analytical Bounds between Entropy and Error Probability in Binary Classifications. CoRR abs/1205.6602 (2012)
Coauthor Index
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