学术论文

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  • [NO.]
    Year / Authors / Paper-Title / Journal / [Month]Year / [Volume-Issue-Pages] / DOI / Citation-numbers (SCI/WOS/Google-Scholar)

    近期接收论文
  • [290]
    (2022) Weipeng Cao, Yuhao Wu, Chengchao Huang, Muhammed J. A. Patwary and Xizhao Wang; MFF: Multi-Modal Feature Fusion for Zero-Shot Learning; Neurocomputing; Accepted in September 2022
  • [289]
    (2022) Chao Liu, Xizhao Wang, Han Liu, Xiaoying Zou, Si Cen, and Guoquan Dai; Learning to Recommend Journals for Submission Based on Embedding Models; Neurocomputing; Accepted in August 2022
  • [288]
    (2022) Shuyue Chen, Ran Wang, Jian Lu, and Xizhao Wang; Stable Matching-Based Two-Way Selection in Multi-Label Active Learning with Imbalanced Data; Information Sciences; Accepted in July 2022
  • [287]
    (2022) Yanting Guo, Meng Hu, Xizhao Wang, Eric C.C. Tsang, Degang Chen, and Weihua Xu; A robust approach to attribute reduction based on double fuzzy consistency measure; Knowledge-Based Systems; Accepted in July 2022
  • [286]
    (2022) Ying Zhao, Shuang Li, Rui Zhang, Chi Harold Liu, Weipeng Cao, Xizhao Wang and Song Tian; Semantic Correlation Transfer for Heterogeneous Domain Adaptation; IEEE Transactions on Neural Networks and Learning Systems, Accepted in August 2022; DOI: 10.1109/TNNLS.2022.3199619
  • [285]
    (2022) Jianhua Dai, Xiongtao Zou, Yuhua Qian, Xizhao Wang; Multi-Fuzzy Beta-Covering Approximation Spaces and Their Information Measures; IEEE Transactions on Fuzzy Systems; Accepted in July 2022; DOI: 10.1109/TFUZZ.2022.3193448 (0/0/0)
  • [284]
    (2022) Farhad Pourpanah, Moloud Abdar, Yuxuan Luo, Xinlei Zhou, Ran Wang, Chee Peng Lim, Xizhao Wang; A Review of Generalized Zero-Shot Learning Methods; IEEE Transactions on Pattern Analysis and Machine Intelligence; Accepted in July 2022 (0/0/36)
  • [283]
    (2022) Guoquan Dai, Xizhao Wang, Xiaoying Zou, Chao Liu, Si Cen; MRGAT: Multi-Relational Graph Attention Network for Knowledge Graph Completion; Neural Networks; Accepted in July 2022 (0/0/0)
  • [282]
    (2022) Xiaoying Zou, Xizhao Wang, Si Cen, Guoquan Dai, Chao Liu; Knowledge graph embedding with self-adaptive double-limited loss; Knowledge-Based Systems; Accepted in June 2022. DOI: https://doi.org/10.1016/j.knosys.2022.109310 (0/0/0)
  • [281]
    (2022) Wentao Li, Haoxiang Zhou, Weihua Xu, Xizhao Wang, Witold Pedrycz; Interval Dominance-Based Feature Selection for Interval-Valued Ordered Data; IEEE Transactions on Neural Networks and Learning Systems; Accepted in June 2022. (0/0/0)
  • [280]
    (2022) Min Wang, Chunyu Yang, Fei Zhao, Fan Min, Xizhao Wang; Cost-Sensitive Active Learning for Incomplete Data; IEEE Transactions on Systems, Man and Cybernetics: Systems; Accepted in June 2022. (0/0/0)
  • [279]
    (2022) Juncheng Li, Faming Fang, Tieyong Zeng, Guixu Zhang, Xizhao Wang; Adjustable Super-Resolution Network via Deep Supervised Learning and Progressive Self-Distillation; Neurocomputing; Accepted in May 2022. (0/0/0)
  • [278]
    (2022) Farhad Pourpanah, Ran Wang, Chee Peng Lim, Xi-Zhao Wang, Danial Yazdani, A Review of Artificial Fish Swarm Algorithms: Recent Advances and Applications, Artificial Intelligence Review. Accepted in May 2022.
  • [277]
    (2022) Muhammed J. A. Patwary, Weipeng Cao, Xizhao Wang(*), Mohammad Ahsanul Haque. Fuzziness based semi-supervised multimodal learning for patient’s activity recognition using RGBDT videos. Applied Soft Computing. Accepted (available online) 25 February 2022. (0/0/0)
  • [276]
    (2022) Hufsa Khan, Xizhao Wang, Han Liu(*). Handling missing data through deep convolutional neural network. Information Sciences. Accepted in February 2022. Available online 1 March 2022. https://doi.org/10.1016/j.ins.2022.02.051. (0/0/0)
  • [275]
    (2022) Sihong Chen, Haojing Shen, Ran Wang, Xizhao Wang(*). Towards improving fast adversarial training in multi-exit network. Neural Networks. Accepted in February 2022. https://doi.org/10.1016/j.neunet.2022.02.015 (0/0/0)
  • [274]
    (2022) Haojing Shen, Sihong Chen, Ran Wang, Xizhao Wang(*). Adversarial Learning with Cost-Sensitive Classes. IEEE Transactions on Cybernetics. Accepted in January 2022. doi: https://doi.org/10.1109/TCYB.2022.3146388 (0/0/0)
  • [273]
    (2020) 陈思宏,沈浩靖,王冉,王熙照,预测不确定性与对抗鲁棒性的关系研究,软件学报,33(2):524-538. (0/0/0)

    IEEE 论文
  • [272]
    (2021)Mei Yang, Yu-Xuan Zhang, Xizhao Wang and Fan Min(*). Multi-Instance Ensemble Learning with Discriminative Bags. IEEE Transactions on Systems Man & Cybernetics: Systems. Accepted in November 2021, doi: https://doi.org/10.1109/TSMC.2021.3125040 (0/0/0)
  • [271]
    (2022) Hong Zhu, Xizhao Wang(*) and Ran Wang(*). Fuzzy Monotonic K-Nearest Neighbor versus Monotonic Fuzzy K-Nearest Neighbor. IEEE Transactions on Fuzzy Systems, September 2022, Volume 30, Issue 9, Pages 3501-3513. DOI: https://doi.org/10.1109/TFUZZ.2021.3117450 (0/0/0)
  • [270]
    (2021) Suyun Zhao(*), Zhigang Dai, Xizhao Wang, Peng Ni, Hengheng Luo, Hong Chen, Cuiping Li, An Accelerator for Rule Induction in Fuzzy Rough Theory, IEEE Transactions on Fuzzy Systems, Vol.29 (12), 3635-3649, December 2021, DOI: https://doi.org/10.1109/TFUZZ.2021.3101935
  • [269]
    (2021) Jianhui Pang, Yanghui Rao(*), Haoran Xie, Xizhao Wang, Fu Lee Wang, Tak-Lam Wong, Qing Li, Fast Supervised Topic Models for Short Text Emotion Detection. IEEE Transactions on Cybernetics, February 2021, 51(2): 815-828, doi: https://doi.org/10.1109/TCYB.2019.2940520 (4/4/13)
  • [268]
    (2020) Dongmei Mo, Zhihui Lai, Waikeung Wong(*), Xizhao Wang. Jointly Sparse Locality Regression for Image Feature Extraction. IEEE Transactions on Multimedia, November 2020, 22(11): 2873-2888, doi: https:// doi.org/10.1109/TMM.2019.2961508 (0/0/1)
  • [267]
    (2020) Lei Zhang(*), Qingyan Duan, David Zhang, Wei Jia, Xizhao Wang. AdvKin: Adversarial Convolutional Network for Kinship Verification. IEEE Transactions on Cybernetics, December 2021, 51(12):5883-5896, 1-14 doi: https:// doi.org/10.1109/TCYB.2019.2959403 (7/7/16)
  • [266]
    (2019) Qin Lin, Huailing Zhang, Xizhao Wang(*), Yun Xue, Hongxin Liu, Changwei Gong. A Novel Parallel Biclustering Approach and Its Application to Identify and Segment Highly Profitable Telecom Customers. IEEE Access, December 2019, 7(1): 28696-28711, doi: https://doi.org/10.1109/ACCESS.2019.2898644 (2/2/7)
  • [265]
    (2019) Rong Chen, Shikai Guo, Xizhao Wang(*), Tianlun Zhang. Fusion of Multi-RSMOTE with Fuzzy Integral to Classify Bug Reports with an Imbalanced Distribution. IEEE Transactions on Fuzzy Systems, December 2019, 27(12):2406-2420, doi: https://doi.org/10.1109/TFUZZ.2019.2899809 (49/49/55)
  • [264]
    (2019) Salim Rezvani, Xizhao Wang(*), Farhad Pourpanah. Intuitionistic Fuzzy Twin Support Vector Machines. IEEE Transactions on Fuzzy Systems, November 2019, 27(11):2140-2151, doi: https://doi.org/10.1109/TFUZZ.2019.2893863 (26/28/41)
  • [263]
    (2019)Laizhong Cui, Chong Xu, Shu Yang(*), Joshua Zhexue Huang, Jianqiang Li, Xizhao Wang, Zhong Ming, Nan Lu. Joint Optimization of Energy Consumption and Latency in Mobile Edge Computing for Internet of Things. IEEE Internet of Things Journal, June 2019, 6(3): 4791-4803, doi: https://doi.org/10.1109/JIOT.2018.2869226 (40/42/59)
  • [262]
    (2019) Wing W.Y. Ng, Xing Tian(*), Witold Pedrycz, Xizhao Wang, Daniel S. Yeung. Incremental Hash-bit Learning for Semantic Image Retrieval in Non-stationary Environments. IEEE Transactions on Cybernetics, November 2019, 49: 3844-3858, doi: https://doi.org/10.1109/TCYB.2018.2846760 (0/0/10)
  • [261]
    (2019) Xiaojun Chen(*), Wenya Sun, Bo Wang, Zhihui Li, Xizhao Wang, Yunming Ye. Spectral Clustering of Customer Transaction Data With a Two-Level Subspace Weighting Method. IEEE Transactions on Cybernetics, September 2019, 49(9):3230-3241, doi: https://doi.org/10.1109/TCYB.2018.2836804 (9/9/19)
  • [260]
    (2019) Wing W. Y. Ng, Jianjun Zhang, Chun Sing Lai(*), Witold Pedrycz, Loi Lei Lai(*), and Xizhao Wang. Cost-Sensitive Weighting and Imbalance-Reversed Bagging for Streaming Imbalanced and Concept Drifting in Electricity Pricing Classification. IEEE Transactions on Industrial Informatics, March 2019, 15(3):1588-1597, doi: https://doi.org/10.1109/TII.2018.2850930 (15/15/21)
  • [259]
    (2019) Xizhao Wang, Tianlun Zhang, Ran Wang(*). Noniterative Deep Learning: Incorporating Restricted Boltzmann Machine into Multilayer Random Weight Neural Networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, July 2019, 49(7):1299-1380, doi: https://doi.org/10.1109/TSMC.2017.2701419 (35/35/68)
  • [258]
    (2018) Yanyan Yang(*), Degang Chen, Hui Wang, Xizhao Wang. Incremental perspective for feature selection based on fuzzy rough sets. IEEE Transactions on Fuzzy Systems, June 2018, 26(3):1257-1273, doi: https://doi.org/10.1109/TFUZZ.2017.2718492 (40/42/52)
  • [257]
    (2018) Patrick P. K. Chan, Weiwen Liu, Danni Chen, Daniel S. Yeung, Fei Zhang(*), Xizhao Wang, Chien-Chang Hsu. Face Liveness Detection Using a Flash Against 2D Spoofing Attack. IEEE Transactions on Information Forensis and Security, February 2018, 13(2):521-534, doi: https://doi.org/10.1109/TIFS.2017.2758748 (26/27/52)
  • [256]
    (2018) Xizhao Wang, Ran Wang(*), Chen Xu. Discovering the Relationship Between Generalization and Uncertainty by Incorporating Complexity of Classification. IEEE Transactions on Cybernetics, February 2018, 48(2):703-715,doi: https://doi.org/10.1109/TCYB.2017.2653223 (71/71/85)
  • [255]
    (2017) Changzhong Wang(*), Qinghua Hu, Xizhao Wang, Degang Chen, Yuhua Qian, Zhe Dong. Feature selection based on neighborhood discrimination index. IEEE Transactions on Neural Networks and Learning Systems, July 2017, 29(7):2986-2999, doi: https://doi.org/10.1109/TNNLS.2017.2710422 (112/124/129)
  • [254]
    (2017) Ran Wang, Xizhao Wang (*), Sam Kwong, Chen Xu. Incorporating Diversity and Informativeness in Multiple-Instance Active Learning. IEEE Transactions on Fuzzy Systems, December 2017, 25(6): 1460-1475, doi: https://doi.org/10.1109/TFUZZ.2017.2717803 (65/66/78)
  • [253]
    (2016) Xizhao Wang(*), Yulin He. Learning from Uncertainty for Big Data (Future Analytical Challenges and Strategies). IEEE Systems, Man, and Cybernetics Magazine, April 2016, 2(2): 26-31, doi: https://doi.org/10.1109/MSMC.2016.2557479 (2/2/39)WOS NO FOUND
  • [252]
    (2015) Xi-zhao 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 Transactions on Fuzzy Systems, October 2015, 23(5): 1638-1654, doi: https://doi.org/10.1109/TFUZZ.2014.2371479 (181/188/213)
  • [251]
    (2015) Ran Wang(*), Sam Kwon, Xi-zhao Wang, Qing-Shan Jiang. Segment Based Decision Tree Induction with Continuous Valued Attributes. IEEE Transactions on Cybernetics, July 2015, 45(7): 1262-1275, doi: https://doi.org/10.1109/TCYB.2014.2348012 (53/55/57)
  • [250]
    (2014) Xi-zhao Wang(*), Ran Wang, Hui-Min Feng, Huachao Wang. A new approach to classifier fusion based on upper integral. IEEE Transactions on Cybernetics, March 2014, 44(5): 620-635, doi: https://doi.org/10.1109/TCYB.2013.2263382 (36/36/42)
  • [249]
    (2014) Xi-zhao Wang(*), Yu-Lin He, Dabby D. Wang. Non-Naive Bayesian Classifiers for Classification Problems with Continuous Attributes. IEEE Transactions on Cybernetics, January 2014, 44(1): 21-39, doi: https://doi.org/10.1109/TCYB.2013.2245891 (66/70/90)
  • [248]
    (2014) Huimin Feng and Xizhao Wang(*). Performance Improvement of Classifier Fusion for Batch Samples Based on Upper Integral. Neural Networks, March 2015, 63: 87-93, doi: https://doi.org/10.1016/j.neunet.2014.11.004 (6/6/7)
  • [247]
    (2012) Xizhao Wang(*), Lingcai Dong, Jianhui Yan. Maximum ambiguity based sample selection in fuzzy decision tree induction. IEEE Transactions on Knowledge and Data Engineering, August 2012, 24(8): 1491-1505, doi: https://doi.org/10.1109/TKDE.2011.67 (127/133/168)
  • [246]
    (2010) Suyun Zhao(*), Eric C. C. Tsang, Degang Chen, Xizhao Wang. Building a rule-based classifier-a fuzzy-rough set approach, IEEE Transactions on Knowledge and Data Engineering, May 2010, 22(5): 624-638, doi: https://doi.org/10.1109/TKDE.2009.118 (87/93/115)
  • [245]
    (2009) Xizhao Wang(*), Chunru Dong. Improving generalization of fuzzy if-then rules by maximizing fuzzy entropy. IEEE Transactions on Fuzzy Systems, June2009, 17(3): 556-567, doi: https://doi.org/10.1109/TFUZZ.2008.924342 (160/161/207)
  • [244]
    (2008) Xizhao Wang(*), Feng Guo, Xianghui Gao. Task 2 winner's solution: A Minkowski distance and nearest-unlike-neighbor distance method, within the paper “ Qiang Yang, et al, Estimating location using Wi-Fi”. IEEE Intelligent Systems, 2008, 23(1): 8-13
  • [243]
    (2007) Daniel Yeung(*), Shuyuan Jin, Xizhao Wang. Covariance-matrix modeling and detecting various flooding attacks. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, March 2007, 37(2): 157-169, doi: https://doi.org/10.1109/TSMCA.2006.889480 (43/44/83)
  • [242]
    (2007) DS Yeung(*), Ng Wing, Defeng Wang, Eric Tsang, Xizhao Wang. Localized generalization error model and its application to architecture selection for radial basis function neural network. IEEE Transactions on Neural Networks, September 2007, 18(5): 1294-1305, doi: https://doi.org/10.1109/TNN.2007.894058 (106/110/191)
  • [241]
    (2005) DS Yeung(*), Degang Chen, ECC Tsang, JWT Lee, Xizhao Wang. On the generalization of fuzzy rough sets. IEEE Transactions on Fuzzy Systems, June 2005, 13(3): 343-361, doi: https://doi.org/10.1109/TFUZZ.2004.841734 (312/330/449)
  • [240]
    (2004) ECC Tsang(*), DS Yeung, JWT Lee, DM Huang, Xizhao Wang. Refinement of generated fuzzy production rules by using a fuzzy neural network. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, February 2004, 34(1): 409-418, doi: https://doi.org/10.1109/TSMCB.2003.817033 (18/19/34)
  • [239]
    (2004) DS Yeung(*), Xizhao Wang, ECC Tsang. Handling interaction in fuzzy production rule reasoning. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, October 2004, 34(5): 1979-1987, doi: https://doi.org/10.1109/TSMCB.2004.831460 (15/16/44)
  • [238]
    (2003) ECC Tsang(*), DS Yeung, Xizhao Wang. OFFSS: Optimal fuzzy-valued feature subset selection. IEEE Transactions on Fuzzy Systems, April 2003, 11(2): 202-213, doi: https://doi.org/10.1109/TFUZZ.2003.809895 (36/37/69)
  • [237]
    (2002) DS Yeung(*), Xizhao Wang. Improving performance of similarity-based clustering by feature weight learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, April 2002, 24(4): 556-561, doi: https://doi.org/10.1109/34.993562 (75/88/124)
  • [236]
    (2001) Xizhao Wang(*), DS Yeung, ECC Tsang. A comparative study on heuristic algorithms for generating fuzzy decision trees. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, April 2001, 31(2): 215-226, doi: https://doi.org/10.1109/3477.915344 (95/99/180)
  • [235]
    (2000) ECC Tsang(*), Xizhao Wang, DS Yeung. Improving learning accuracy of fuzzy decision trees by hybrid neural networks. IEEE Transactions on Fuzzy Systems, October 2000, 8(5): 601-614, doi: https://doi.org/10.1109/91.873583 (57/59/81)
  •  

    Elsevier 论文
  • [234]
    (2021) Xinlei Zhou, Han Liu, Farhad Pourpanah, Tieyong Zeng and Xizhao Wang(*). A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications. Neurocomputing. Accepted in November 2021 (0/0/0)
  • [233]
    (2021) Salim Rezvani, Xizhao Wang(*). Class imbalance learning using fuzzy ART and intuitionistic fuzzy twin support vector machines. Information Sciences. July 2021, 578:659–682, doi: https://doi.org/10.1016/j.ins.2021.07.010 (1/1/1)
  • [232]
    (2021) Yichao He, Xizhao Wang(*). Group theory-based optimization algorithm for solving knapsack problems. Knowledge-Based Systems. August 2021, 219: 104445, doi: https://doi.org/10.1016/j.knosys.2018.07.045 (11/12/18)
  • [231]
    (2021) Weipeng Cao,Zhongwu Xie,Jianqiang Li,Zhiwu Xu,Zhong Ming,Xizhao Wang(*). Bidirectional Stochastic Configuration Network for Regression Problems. Neural Networks. March 2021, 140:237-246 doi: https://doi.org/10.1016/j.neunet.2021.03.016 (2/2/3)
  • [230]
    (2020) Tianlun Zhang, Xi Yang, Xizhao Wang, Ran Wang(*). Deep Joint Neural Model for Single Image Haze Removal and Color Correction. Information Sciences, December 2020, 541:16-35, doi: https://doi.org/10.1016/j.ins.2020.05.105 (0/0/2)
  • [229]
    (2020) Kai Zhang, Jianming Zhan(*), Xizhao Wang. TOPSIS-WAA method based on a covering-based fuzzy rough set: an application to rating problem. Information Science, October 2020, 539: 397-421, doi: https://doi.org/10.1016/j.ins.2020.06.009 (25/26/30)
  • [228]
    (2020) Jafar Gholami, Farhad Pourpanah, Xizhao Wang(*), Feature selection based on improved binary global harmony search for data classification. Applied Soft Computing, August 2020, 93: 106402, doi: https://doi.org/10.1016/j.asoc.2020.106402 (14/14/19)
  • [227]
    (2019)Peng Ni, Suyun Zhao(*), Xizhao Wang, Hong Chen, Cuiping Li. PARA: A Positive-region based Attribute Reduction Accelerator. Information Science, November 2019, 503: 533-550, doi: https://doi.org/10.1016/j.ins.2019.07.038 (12/13/16)
  • [226]
    (2020) Xinlei Zhou, Xizhao Wang(*), Cong Hu, Ran Wang. An analysis on the relationship between uncertainty and misclassification rate of classifiers. Information Sciences, October 2020, 535: 16-27, doi: https://doi.org/10.1016/j.ins.2020.05.059 (1/1/3)
  • [225]
    (2020) Peng Ni, Suyun Zhao(*), Xizhao Wang, Hong Chen, Cuiping Li, Eric C.C. Tsang. Incremental Feature Selection Based on Fuzzy Rough Sets. Information Sciences, October 2020, 536: 185-204, doi: https://doi.org/10.1016/j.ins.2020.04.038 (10/10/15)
  • [224]
    (2020) Yuxuan Luo, Xizhao Wang(*), Weipeng Cao. A Novel Dataset-Specific Feature Extractor for Zero-Shot Learning. Neurocomputing, May 2020, 391:74-82, doi: https://doi.org/10.1016/j.neucom.2020.01.069 (4/4/6)
  • [223]
    (2020) Xingping Xian, Tao Wu(*), Shaojie Qiao(*), Xi-Zhao Wang, Wei Wang, Yanbing Liu. NetSRE: Link predictability measuring and regulating. Knowledge-Based Systems, May 2020, 196:105800, doi: https://doi.org/10.1016/j.knosys.2020.105800 (4/4/5)
  • [222]
    (2020) MingWen Shao(*), WeiZhi Wu, XiZhao Wang, ChangZhong Wang. Knowledge reduction methods of covering approximate spaces based on concept lattice. Knowledge-Based Systems, March 2020, 191: 105269, doi: https://doi.org/10.1016/j.knosys.2019.105269 (4/4/5)
  • [221]
    (2020) S. Rezvani and Xizhao Wang(*). Erratum to “Entropy-based fuzzy support vector machine for imbalanced datasets" [Knowl.-Based Syst. 115 (2017) 87–99]. Knowledge-Based Systems, March 2020, 192: 105287, doi: https://doi.org/10.1016/j.knosys.2016.09.032 (0/0/3)WOS NO FOUND
  • [220]
    (2020) Tianlun Zhang, Yang Li, Xizhao Wang(*). Gaussian prior based adaptive synthetic sampling with non-linear sample space for imbalanced learning. Knowledge-Based Systems, March 2020, 191: 105231, doi: https://doi.org/10.1016/j.knosys.2019.105231 (2/2/3)
  • [219]
    (2019) Farhad Pourpanah, Ran Wang(*), Chee Peng Lim, Xizhao Wang, Manjeevan Seera, Choo Jun Tan. An Improved Fuzzy ARTMAP and Q-Learning Agent Model for Pattern Classification. Neurocomputing, September 2019, 359: 139-152, doi: https://doi.org/10.1016/j.neucom.2019.06.002 (10/10/17)
  • [218]
    (2019) Dasen Yan, Xinlei Zhou, Xizhao Wang, Ran Wang(*). An Off-centered Technique: Learning a Feature Transformation to Improve the Performance of Clustering and Classification. Information Science, November 2019, 503: 635-651, doi: https://doi.org/10.1016/j.ins.2019.06.068 (2/2/3)
  • [217]
    (2019) Li Zhao, Xizhao Wang(*). Seemingly Unrelated Extreme Learning Machine.Neurocomputing, August 2019, 355:134–142, doi: https://doi.org/10.1016/j.neucom.2019.04.067 (4/4/4)
  • [216]
    Xizhao Wang, Tianlun Zhang, Ran Wang(*). Noniterative Deep Learning: Incorporating Restricted Boltzmann Machine into Multilayer Random Weight Neural Networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, July 2019, 49(7):1299-1380, doi: https://doi.org/10.1109/TSMC.2017.2701419 (27/27/53)
  • [215]
    (2019) Muhammed J.A. Patwary, XiZhao Wang(*). Sensitivity analysis on initial classifier accuracy in fuzziness based semi-supervised learning, Information Sciences, July 2019, 490: 93-112, doi: https://doi.org/10.1016/j.ins.2019.03.036 (8/8/16)
  • [214]
    (2019) Farhad Pourpanah(*), Chee Peng Lim, Xizhao Wang, Choo Jun Tan, Manjeevan Seera, Yuhui Shi. A hybrid model of fuzzy min–max and brain storm optimization for feature selection and data classification. Neurocomputing, March 2019, 333: 440-45, doi: https://doi.org/10.1016/j.neucom.2019.01.011 (24/24/36)
  • [213]
    (2019) Yichao He, Xizhao Wang(*), Suogang Gao. Ring Theory-Based Evolutionary Algorithm and its application to D{0–1}KP. Applied Soft Computing, April 2019, 77: 714–22, doi: https://doi.org/10.1016/j.asoc.2019.01.049 (5/5/9)
  • [212]
    (2018) Huang Z, Wang X(*). Sensitivity of data matrix rank in non-iterative training. Neurocomputing, November 2018, 313(3):386–391, DOI: https://doi.org/10.1016/j.neucom.2018.06.055 (4/4/4)
  • [211]
    (2018) Laizhong Cui, Kai Zhang, Genghui Li(*), XiZhao Wang, Shu Yang. A smart artificial bee colony algorithm with distance-fitness-based neighbor search and its application. Future Generation Computer Systems, December 2018, 89:478-493, doi: https://doi.org/10.1016/j.future.2018.06.054 (15/15/18)
  • [210]
    (2018) Junhai Zhai(*), Xizhao Wang, Sufang Zhang, Shaoxing Houd. Tolerance rough fuzzy decision tree. Information Sciences, October 2018, 465:425-438, doi: https://doi.org/10.1016/j.ins.2018.07.006 (12/12/18)
  • [209]
    (2018) Zhi Wang and Xizhao Wang(*). A deep stochastic weight assignment network and its application to chess playing. Journal of Parallel and Distributed Computing, July 2018, 117: 205-211, doi: https://doi.org/10.1016/j.jpdc.2017.08.013 (8/8/9)
  • [208]
    (2018) Wing W.Y. Ng, Xiancheng Zhou, Xing Tian(*), Xizhao Wang, Daniel S. Yeung. Bagging–boosting-based semi-supervised multi-hashing with query-adaptive re-ranking. Neurocomputing, January 2018, 275:916-923, doi: https://doi.org/10.1016/j.neucom.2017.09.042 (17/18/22)
  • [207]
    (2018) Yichao He, Haoran Xie, Tak-Lam Wong, Xizhao Wang(*), A novel binary artificial bee colony algorithm for the set-union knapsack problem, Future Generation Computer Systems, January 2018, 78: 77-86, doi: https://doi.org/10.1016/j.future.2017.05.044 (50/56/72)
  • [206]
    (2018) Weipeng Cao, Xizhao Wang(*), Zhong Ming, Jinzhu Gao. A Review on Neural Networks with Random Weights. Neurocomputing, January 2018, 275:278–287, doi: https://doi.org/10.1016/j.neucom.2017.08.040 (180/182/272)
  • [205]
    (2017) Hongyu Zhu, Xi-Zhao Wang(*). A cost-sensitive semi-supervised learning model based on uncertainty. Neurocomputing, August 2017, 251: 106–114, doi: https://doi.org/10.1016/j.neucom.2017.04.010 (14/17/20)
  • [204]
    (2017) Hong Zhu, Eric Tsang(*), Xizhao Wang, Rana Aamir Raza Ashfaq. Monotonic classification Extreme Learning Machine. Neurocomputing, February 2017, 225: 205–213, doi: https://doi.org/10.1016/j.neucom.2016.11.021 (26/28/35)
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    (2004) Wing Ng(*), Daniel Yeung, Xizhao Wang, Ian Cloete. A study of the difference between partial derivative and stochastic neural network sensitivity analysis for applications in supervised pattern classification problems. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August 2004, Proceedings pp: 4283-4288, doi: https://doi.org/10.1109/ICMLC.2004.1384590 (0,5,15)
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    (2003) Yan Li(*), Xizhao Wang, Minghu Ha. On-line multi-CBR agent dispatching. Proceedings of 2003 International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 2071-2075, doi: https://doi.org/10.1109/ICMLC.2003.1259845 (0,1,4)
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    (2002) Shenshan Qiu(*), Eric C.C. Tsang, Daniel S. Yeung, Xizhao Wang. Energy Function Criterion for Discrete Hopfield-Type Neural Network with Delay. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 2240-2244, doi: https://doi.org/10.1109/ICMLC.2002.1175438 (0,0,0)
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    (2001) Ruifeng Xu(*), D. S. Yeung, Xizhao Wang. Using neural network classifier in post-processing system for handwritten Chinese character recognition. Proceedings of 2001 IEEE International Conference on Systems, Man and Cybernetics, Tucson, AZ, USA, 07-10 October 2001, Proceedings pp: 1497-1502, doi: https://doi.org/10.1109/ICSMC.2001.973493 (0,0,7)
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    (2000) Xizhao Wang(*), D. S. Yeung. Using fuzzy integral to modeling case based reasoning with feature interaction. Proceedings of 2000 IEEE International Conference on Systems, Man and Cybernetics, Nashville, TN, USA, 8-11 October 2000, Proceedings pp: 3660-3665, doi: https://doi.org/10.1109/ICSMC.2000.886578 (9,0,23)
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    (2000) D. S. Yeung(*), Xizhao Wang. Using a neuro-fuzzy technique to improve the clustering based on similarity. Proceedings of 2000 IEEE International Conference on Systems, Man and Cybernetics, Nashville, TN, USA, 8-11 October 2000, Proceedings pp: 3693-3698, doi: https://doi.org/10.1109/ICSMC.2000.886584 (1,0,9)

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