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ORCIDHan Liu 0002
Person information
- affiliation: Shenzhen University, Guangdong, China
- affiliation (former): Cardiff University, School of Computer Science and Informatics, UK
- affiliation (PhD 2015): University of Portsmouth, School of Computing, UK
Other persons with the same name
- Han Liu — disambiguation page
- Han Liu 0001
![[0000-0002-2470-1755]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-2470-1755")
— Northwestern University, Evanston, IL, USA (and 4 more) - Han Liu 0003 — King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Han Liu 0004 — Harbin Institute of Technology, School of Transportation Science and Engineering, China
- Han Liu 0005 — Sun Yat-Sen University, School of Geography and Planning, Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, Guangzhou, China
- Han Liu 0006 — Southeast University, School of Electrical Engineering, Nanjing, China (and 1 more)
- Han Liu 0007 — Xi'an University of Technology, Faculty of Automation and Information Engineering, Xi'an, China (and 1 more)
- Han Liu 0008 — Dalian University of Technology, School of Software, Dalian, China (and 1 more)
- Han Liu 0009 — Shanghai Maritime University, College of Information Engineering, Shanghai, China
- Han Liu 0010 — Oxford-Hainan Blockchain Research Institute, Haikou, China (and 2 more)
- Han Liu 0011 — Advanced Micro Devices (AMD) Inc., Beijing, China
- Han Liu 0012 — Hong Kong University of Science and Technology, Hong Kong (and 1 more)
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2020 – today
- 2024
[j30]Hufsa Khan, Muhammad Tahir Rasheed, Han Liu, Shengli Zhang:
High-order polynomial interpolation with CNN: A robust approach for missing data imputation. Comput. Electr. Eng. 119: 109524 (2024)- [j29]Hufsa Khan, Muhammad Tahir Rasheed, Shengli Zhang, Xizhao Wang, Han Liu:
Empirical study of outlier impact in classification context. Expert Syst. Appl. 256: 124953 (2024) - [j28]Han Liu, Qianxi Qiu, Qin Zhang:
End-to-end approach of multi-grained embedding of categorical features in tabular data. Inf. Process. Manag. 61(2): 103645 (2024) - [c34]Hongwei Su, Han Liu, Weipeng Cao, Zhong Ming:
Knowledge Distillation with Classmate. ICIC (2) 2024: 245-256 - 2023
- [j27]Hufsa Khan, Xizhao Wang, Han Liu:
A study on relationship between prediction uncertainty and robustness to noisy data. Int. J. Syst. Sci. 54(6): 1243-1258 (2023) - [c33]Si Cen, Han Liu, Chao Liu, Xiaoying Zou, Guoquan Dai, Xizhao Wang:
An End-to-End Training Method to Ensemble Bi-Linear Models for Knowledge Graph Completion. ICMLC 2023: 25-30 - [c32]Zhichao Chen, Han Liu, Qin Zhang:
Adaptive Selection of BERT Layer for Multi-Label Text Classification. ICMLC 2023: 434-439 - 2022
- [j26]Xinlei Zhou, Han Liu, Farhad Pourpanah, Tieyong Zeng, Xizhao Wang:
A survey on epistemic (model) uncertainty in supervised learning: Recent advances and applications. Neurocomputing 489: 449-465 (2022) - [j25]Chao Liu, Xizhao Wang, Han Liu, Xiaoying Zou, Si Cen, Guoquan Dai:
Learning to recommend journals for submission based on embedding models. Neurocomputing 508: 242-253 (2022) - [j24]Hufsa Khan, Xizhao Wang, Han Liu:
Handling missing data through deep convolutional neural network. Inf. Sci. 595: 278-293 (2022) - [j23]Chengwei Li, Han Liu, Zhong Ming:
Empirical study on virtual order of class labels in nominal classification. Int. J. Mach. Learn. Cybern. 13(11): 3255-3266 (2022) - [j22]Wafa Alorainy, Pete Burnap, Han Liu, Matthew L. Williams, Luca Giommoni:
Disrupting networks of hate: characterising hateful networks and removing critical nodes. Soc. Netw. Anal. Min. 12(1): 27 (2022) - 2021
- [j21]Qiang Li, Yingjian Yang, Yingwei Guo, Wei Li, Yang Liu, Han Liu, Yan Kang:
Performance Evaluation of Deep Learning Classification Network for Image Features. IEEE Access 9: 9318-9333 (2021) - [j20]Patrick P. K. Chan, Juan Zheng, Han Liu, Eric C. C. Tsang, Daniel S. Yeung:
Robustness analysis of classical and fuzzy decision trees under adversarial evasion attack. Appl. Soft Comput. 107: 107311 (2021) - [j19]Hufsa Khan, Xizhao Wang, Han Liu:
Missing value imputation through shorter interval selection driven by Fuzzy C-Means clustering. Comput. Electr. Eng. 93: 107230 (2021) - [j18]Keke Huang, Haofei Wen, Han Liu, Chunhua Yang, Weihua Gui:
A geometry constrained dictionary learning method for industrial process monitoring. Inf. Sci. 546: 265-282 (2021) - [j17]Hailun Xie, Li Zhang, Chee Peng Lim, Yonghong Yu, Han Liu:
Feature Selection Using Enhanced Particle Swarm Optimisation for Classification Models. Sensors 21(5): 1816 (2021) - [e2]Ruidan Su, Yu-Dong Zhang, Han Liu:
Proceedings of 2021 International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2021, Birmingham, United Kingdom, March 25-26, 2021. Lecture Notes in Electrical Engineering 784, Springer 2021, ISBN 978-981-16-3879-4 [contents] - [i2]Xinlei Zhou, Han Liu, Farhad Pourpanah, Tieyong Zeng, Xizhao Wang:
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications. CoRR abs/2111.01968 (2021) - 2020
- [j16]Halefom Tekle Weldegebriel, Han Liu, Anwar Ul Haq, Emmanuel Bugingo, Defu Zhang:
A New Hybrid Convolutional Neural Network and eXtreme Gradient Boosting Classifier for Recognizing Handwritten Ethiopian Characters. IEEE Access 8: 17804-17818 (2020) - [j15]Yanling Zhou, Yanyan Yang, Han Liu, Xiufeng Liu, Nick Savage:
Deep Learning Based Fusion Approach for Hate Speech Detection. IEEE Access 8: 128923-128929 (2020) - [j14]Han Liu, Shyi-Ming Chen:
Heuristic creation of deep rule ensemble through iterative expansion of feature space. Inf. Sci. 520: 195-208 (2020) - [j13]Weili Ding, Bo Hu, Han Liu, Xinming Wang, Xiangsheng Huang:
Human posture recognition based on multiple features and rule learning. Int. J. Mach. Learn. Cybern. 11(11): 2529-2540 (2020) - [c31]Han Liu, Pete Burnap, Wafa Alorainy, Matthew L. Williams:
Scmhl5 at TRAC-2 Shared Task on Aggression Identification: Bert Based Ensemble Learning Approach. TRAC@LREC 2020: 62-68 - [c30]Fraser Young, Li Zhang, Richard Jiang, Han Liu, Conor Wall:
A Deep Learning Based Wearable Healthcare Iot Device for AI-Enabled Hearing Assistance Automation. ICMLC 2020: 235-240 - [c29]Michael Willis, Li Zhang, Han Liu, Hailun Xie, Kamlesh Mistry:
Object Recognition Using Enhanced Particle Swarm Optimization. ICMLC 2020: 241-246 - [c28]Ziwen Wang, Haiming Wu, Han Liu, Qian-Hua Cai:
Bert-Pair-Networks for Sentiment Classification. ICMLC 2020: 273-278 - [e1]Ruidan Su, Han Liu:
Proceedings of 2020 International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2020, Oxford, UK, January 20-21, 2020. Lecture Notes in Electrical Engineering 633, Springer 2020, ISBN 978-981-15-5198-7 [contents] - [i1]Fraser Young, Li Zhang, Richard Jiang, Han Liu, Conor Wall:
A Deep Learning based Wearable Healthcare IoT Device for AI-enabled Hearing Assistance Automation. CoRR abs/2005.08076 (2020)
2010 – 2019
- 2019
- [j12]Hailun Xie, Li Zhang, Chee Peng Lim, Yonghong Yu, Chengyu Liu, Han Liu, Julie Walters:
Improving K-means clustering with enhanced Firefly Algorithms. Appl. Soft Comput. 84 (2019) - [j11]Han Liu, Li Zhang:
Advancing Ensemble Learning Performance through data transformation and classifiers fusion in granular computing context. Expert Syst. Appl. 131: 20-29 (2019) - [j10]Han Liu, Shyi-Ming Chen, Mihaela Cocea:
Subclass-based semi-random data partitioning for improving sample representativeness. Inf. Sci. 478: 208-221 (2019) - [j9]Han Liu, Shyi-Ming Chen, Mihaela Cocea:
Heuristic target class selection for advancing performance of coverage-based rule learning. Inf. Sci. 479: 164-179 (2019) - [j8]Han Liu, Shyi-Ming Chen:
Multi-stage mixed rule learning approach for advancing performance of rule-based classification. Inf. Sci. 495: 65-77 (2019) - [j7]Han Liu, Pete Burnap, Wafa Alorainy, Matthew L. Williams:
A Fuzzy Approach to Text Classification With Two-Stage Training for Ambiguous Instances. IEEE Trans. Comput. Soc. Syst. 6(2): 227-240 (2019) - [j6]Wafa Alorainy, Pete Burnap, Han Liu, Matthew L. Williams:
"The Enemy Among Us": Detecting Cyber Hate Speech with Threats-based Othering Language Embeddings. ACM Trans. Web 13(3): 14:1-14:26 (2019) - [c27]Han Liu, Shyi-Ming Chen:
Multi-Task Ensemble Creation for Advancing Performance of Image Segmentation. ICMLC 2019: 1-7 - [c26]Han Liu, Shyi-Ming Chen:
Multi-Perspective Creation of Diversity for Image Classification In Ensemble Learning Context. ICMLC 2019: 1-6 - [c25]Ting Yuan, Hai-Hui Li, Hong-Ya Zhao, Qian-Hua Cai, Han Liu, Xiao-Hui Hu:
Multi-Channel Convolutional Neural Network for Targeted Sentiment Classification. ICMLC 2019: 1-6 - [c24]Han Liu, Shyi-Ming Chen:
Multi-Level Creation of Fuzzy Ensembles through Diversified Settings of Parameters. ISCID (1) 2019: 185-188 - [c23]Fatima Chiroma, Mihaela Cocea, Han Liu:
Detection of Suicidal Twitter Posts. UKCI 2019: 307-318 - [c22]Han Liu, Pete Burnap, Wafa Alorainy, Matthew L. Williams:
Fuzzy Multi-task Learning for Hate Speech Type Identification. WWW 2019: 3006-3012 - 2018
- [j5]Zhenfeng Lei, Shuangyuan Yang, Han Liu, Saba Aslam, Jinyu Liu, Halefom Tekle Weldegebriel, Emmanuel Bugingo, Defu Zhang:
Mining of Nutritional Ingredients in Food for Disease Analysis. IEEE Access 6: 52766-52778 (2018) - [j4]Han Liu, Mihaela Cocea:
Induction of classification rules by Gini-index based rule generation. Inf. Sci. 436-437: 227-246 (2018) - [c21]Han Liu, Mihaela Cocea:
Fuzzy rule based systems for gender classification from blog data. ICACI 2018: 79-84 - [c20]Fatima Chiroma, Mihaela Cocea, Han Liu:
Evaluation of Rule-Based Learning and Feature Selection Approaches For Classification. ICCSW 2018: 6:1-6:6 - [c19]Han Liu, Mihaela Cocea, Weili Ding:
J-Measure Based Pruning for Advancing Classification Performance of Information Entropy Based Rule Generation. ICMLC 2018: 485-490 - [c18]Fatima Chiroma, Han Liu, Mihaela Cocea:
Suiciderelated Text Classification With Prism Algorithm. ICMLC 2018: 575-580 - [c17]Wafa Alorainy, Pete Burnap, Han Liu, Amir Javed, Matthew L. Williams:
Suspended Accounts: A Source of Tweets with Disgust and Anger Emotions for Augmenting Hate Speech Data Sample. ICMLC 2018: 581-586 - [c16]Fatima Chiroma, Han Liu, Mihaela Cocea:
Text Classification For Suicide Related Tweets. ICMLC 2018: 587-592 - [c15]Alaa Mohasseb, Mohamed Bahy Bader-El-Den, Mihaela Cocea, Han Liu:
Improving Imbalanced Question Classification Using Structured Smote Based Approach. ICMLC 2018: 593-597 - [c14]Han Liu, Shyi-Ming Chen:
Multi-Level Fusion of Classifiers Through Fuzzy Ensemble Learning. ISCID (2) 2018: 19-22 - [c13]Han Liu, Fatima Chiroma, Mihaela Cocea:
Identification and Classification of Misogynous Tweets Using Multi-classifier Fusion. IberEval@SEPLN 2018: 268-273 - 2017
- [j3]Han Liu, Alexander E. Gegov, Mihaela Cocea:
Rule Based Networks: An Efficient and Interpretable Representation of Computational Models. J. Artif. Intell. Soft Comput. Res. 7(2): 111 (2017) - [c12]Chris Jefferson, Han Liu, Mihaela Cocea:
Fuzzy approach for sentiment analysis. FUZZ-IEEE 2017: 1-6 - [c11]Han Liu, Mihaela Cocea, Alaa Mohasseb, Mohamed Bader:
Transformation of discriminative single-task classification into generative multi-task classification in machine learning context. ICACI 2017: 66-73 - [c10]Han Liu, Mihaela Cocea:
Fuzzy rule based systems for interpretable sentiment analysis. ICACI 2017: 129-136 - [c9]Han Liu, Mihaela Cocea, Weili Ding:
Decision tree learning based feature evaluation and selection for image classification. ICMLC 2017: 569-574 - [c8]Alaa Mohasseb, Mohamed Bader-El-Den, Han Liu, Mihaela Cocea:
Domain specific syntax based approach for text classification in machine learning context. ICMLC 2017: 658-663 - 2016
- [j2]Han Liu, Alexander E. Gegov, Mihaela Cocea:
Collaborative rule generation: An ensemble learning approach. J. Intell. Fuzzy Syst. 30(4): 2277-2287 (2016) - [c7]Han Liu, Alexander E. Gegov, Mihaela Cocea:
Nature and biology inspired approach of classification towards reduction of bias in machine learning. ICMLC 2016: 588-593 - [c6]Han Liu, Alexander E. Gegov:
Rule based systems and networks: Deterministic and fuzzy approaches. IEEE Conf. on Intelligent Systems 2016: 316-321 - [c5]Han Liu, Alexander E. Gegov, Mihaela Cocea:
Complexity Control in Rule Based Models for Classification in Machine Learning Context. UKCI 2016: 125-143 - [p1]Han Liu, Mihaela Cocea, Alexander E. Gegov:
Interpretability of Computational Models for Sentiment Analysis. Sentiment Analysis and Ontology Engineering 2016: 199-220 - 2015
- [b1]Han Liu:
Rule based systems for classification in machine learning context. University of Portsmouth, UK, 2015 - [c4]Han Liu, Alexander E. Gegov, Mihaela Cocea:
Network based rule representation for knowledge discovery and predictive modelling. FUZZ-IEEE 2015: 1-8 - [c3]Han Liu, Alexander E. Gegov, Mihaela Cocea:
Hybrid ensemble learning approach for generation of classification rules. ICMLC 2015: 377-382 - 2014
- [c2]Han Liu, Alexander E. Gegov, Frederic T. Stahl:
Categorization and Construction of Rule Based Systems. EANN 2014: 183-194 - 2012
- [j1]Frederic T. Stahl, Mohamed Medhat Gaber, Paul Aldridge, David May, Han Liu, Max Bramer, Philip S. Yu:
Homogeneous and Heterogeneous Distributed Classification for Pocket Data Mining. Trans. Large Scale Data Knowl. Centered Syst. 5: 183-205 (2012) - 2011
- [c1]Frederic T. Stahl, Mohamed Medhat Gaber, Han Liu, Max Bramer, Philip S. Yu:
Distributed Classification for Pocket Data Mining. ISMIS 2011: 336-345
Coauthor Index
aka: Mihaela Cocea
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last updated on 2024-11-19 21:41 CET by the dblp team
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