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ORCIDGuangquan Zhang 0001
Person information
- affiliation: University of Technology Sydney, Faculty of Engineering and Information Technology, Centre for Artificial Intelligence, NSW, Australia
- affiliation (PhD 2000): Curtin University of Technology, Department of Mathematics and Statistics, Perth, WA, Australia
- affiliation (1979 - 1997): Hebei University, Baoding, China
Other persons with the same name
- Guangquan Zhang 0002 — Soochow University, Suzhou, China
- Guangquan Zhang 0003
![[0009-0004-0385-1852]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0009-0004-0385-1852")
— Wuhan University of Science and Technology, Department of Resource and Environmental Engineering, China
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2020 – today
- 2024
[j214]Ningyuan Zhang, Jie Lu, Keqiuyin Li, Zhen Fang, Guangquan Zhang:
Source-Free Unsupervised Domain Adaptation: Current research and future directions. Neurocomputing 564: 126921 (2024)- [j213]Kun Wang, Li Xiong, Anjin Liu, Guangquan Zhang, Jie Lu:
A self-adaptive ensemble for user interest drift learning. Neurocomputing 577: 127308 (2024) - [j212]Haotian Xu, Junyu Xuan, Guangquan Zhang, Jie Lu:
Trust region policy optimization via entropy regularization for Kullback-Leibler divergence constraint. Neurocomputing 589: 127716 (2024) - [j211]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Multi-source domain adaptation handling inaccurate label spaces. Neurocomputing 594: 127824 (2024) - [j210]Zhaoqing Liu, Guangquan Zhang, Jie Lu:
Semi-supervised heterogeneous domain adaptation for few-sample credit risk classification. Neurocomputing 596: 127948 (2024) - [j209]Tianyu Liu, Jie Lu, Zheng Yan, Guangquan Zhang:
Robust Gaussian Process Regression With Input Uncertainty: A PAC-Bayes Perspective. IEEE Trans. Cybern. 54(2): 962-973 (2024) - [j208]Guangzhi Ma, Jie Lu, Feng Liu, Zhen Fang, Guangquan Zhang:
Multiclass Classification With Fuzzy-Feature Observations: Theory and Algorithms. IEEE Trans. Cybern. 54(2): 1048-1061 (2024) - [j207]Zhen Fang, Jie Lu, Guangquan Zhang:
An Extremely Simple Algorithm for Source Domain Reconstruction. IEEE Trans. Cybern. 54(3): 1921-1933 (2024) - [j206]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Multidomain Adaptation With Sample and Source Distillation. IEEE Trans. Cybern. 54(4): 2193-2205 (2024) - [j205]Zihe Liu, Jie Lu, Junyu Xuan, Guangquan Zhang:
Deep Reinforcement Learning in Nonstationary Environments With Unknown Change Points. IEEE Trans. Cybern. 54(9): 5191-5204 (2024) - [j204]Guangzhi Ma, Jie Lu, Guangquan Zhang:
Multisource Domain Adaptation With Interval-Valued Target Data via Fuzzy Neural Networks. IEEE Trans. Fuzzy Syst. 32(5): 3094-3106 (2024) - [j203]Guangzhi Ma, Jie Lu, Feng Liu, Zhen Fang, Guangquan Zhang:
Domain Adaptation With Interval-Valued Observations: Theory and Algorithms. IEEE Trans. Fuzzy Syst. 32(5): 3107-3120 (2024) - [j202]Jie Lu, Guangzhi Ma, Guangquan Zhang:
Fuzzy Machine Learning: A Comprehensive Framework and Systematic Review. IEEE Trans. Fuzzy Syst. 32(7): 3861-3878 (2024) - [j201]Kuo Shi, Jie Lu, Zhen Fang, Guangquan Zhang:
Unsupervised Domain Adaptation Enhanced by Fuzzy Prompt Learning. IEEE Trans. Fuzzy Syst. 32(7): 4038-4048 (2024) - [j200]Kezhi Lu, Qian Zhang, Danny Hughes, Guangquan Zhang, Jie Lu:
AMT-CDR: A Deep Adversarial Multi-Channel Transfer Network for Cross-Domain Recommendation. ACM Trans. Intell. Syst. Technol. 15(4): 87:1-87:26 (2024) - [c165]En Yu, Jie Lu, Bin Zhang, Guangquan Zhang:
Online Boosting Adaptive Learning under Concept Drift for Multistream Classification. AAAI 2024: 16522-16530 - [c164]Kuo Shi, Jie Lu, Zhen Fang, Guangquan Zhang:
Enhancing Vision-Language Models Incorporating TSK Fuzzy System for Domain Adaptation. FUZZ 2024: 1-8 - [c163]Bo Peng, Zhen Fang, Guangquan Zhang, Jie Lu:
Knowledge Distillation with Auxiliary Variable. ICML 2024 - [c162]Yunzhuang Shen, Yuan Sun, Xiaodong Li, Zhiguang Cao, Andrew C. Eberhard, Guangquan Zhang:
Adaptive Stabilization Based on Machine Learning for Column Generation. ICML 2024 - [c161]Kuo Shi, Jie Lu, Zhen Fang, Guangquan Zhang:
CLIP-Enhanced Unsupervised Domain Adaptation with Consistency Regularization. IJCNN 2024: 1-8 - [i33]Yi Zhang, Mengjia Wu, Guangquan Zhang, Jie Lu:
Responsible AI: Portraits with Intelligent Bibliometrics. CoRR abs/2405.02846 (2024) - [i32]Yunzhuang Shen, Yuan Sun, Xiaodong Li, Zhiguang Cao, Andrew C. Eberhard, Guangquan Zhang:
Adaptive Stabilization Based on Machine Learning for Column Generation. CoRR abs/2405.11198 (2024) - [i31]Feng Gu, Jie Lu, Zhen Fang, Kun Wang, Guangquan Zhang:
A Neighbor-Searching Discrepancy-based Drift Detection Scheme for Learning Evolving Data. CoRR abs/2405.14153 (2024) - [i30]Zihe Liu, Jie Lu, Guangquan Zhang, Junyu Xuan:
A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points. CoRR abs/2405.14214 (2024) - [i29]Guohang Zeng, Qian Zhang, Guangquan Zhang, Jie Lu:
Sharpness-Aware Cross-Domain Recommendation to Cold-Start Users. CoRR abs/2408.01931 (2024) - 2023
- [j199]Haotian Xu, Zheng Yan, Junyu Xuan, Guangquan Zhang, Jie Lu:
Improving proximal policy optimization with alpha divergence. Neurocomputing 534: 94-105 (2023) - [j198]Yi Zhang, Mengjia Wu, Guangquan Zhang, Jie Lu:
Stepping beyond your comfort zone: Diffusion-based network analytics for knowledge trajectory recommendation. J. Assoc. Inf. Sci. Technol. 74(7): 775-790 (2023) - [j197]Kairui Guo, Mengjia Wu, Zelia Soo, Yue Yang, Yi Zhang, Qian Zhang, Hua Lin, Mark Grosser, Deon Venter, Guangquan Zhang, Jie Lu:
Artificial intelligence-driven biomedical genomics. Knowl. Based Syst. 279: 110937 (2023) - [j196]Zhen Fang, Jie Lu, Feng Liu, Guangquan Zhang:
Semi-Supervised Heterogeneous Domain Adaptation: Theory and Algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 1087-1105 (2023) - [j195]Hang Yu, Weixu Liu, Jie Lu, Yimin Wen, Xiangfeng Luo, Guangquan Zhang:
Detecting group concept drift from multiple data streams. Pattern Recognit. 134: 109113 (2023) - [j194]Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang, Li Xiong:
Evolving Gradient Boost: A Pruning Scheme Based on Loss Improvement Ratio for Learning Under Concept Drift. IEEE Trans. Cybern. 53(4): 2110-2123 (2023) - [j193]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Source-Free Multidomain Adaptation With Fuzzy Rule-Based Deep Neural Networks. IEEE Trans. Fuzzy Syst. 31(12): 4180-4194 (2023) - [j192]Fujin Zhu, Jie Lu, Adi Lin, Junyu Xuan, Guangquan Zhang:
Direct Learning With Multi-Task Neural Networks for Treatment Effect Estimation. IEEE Trans. Knowl. Data Eng. 35(3): 2457-2470 (2023) - [j191]Qian Zhang, Wenhui Liao, Guangquan Zhang, Bo Yuan, Jie Lu:
A Deep Dual Adversarial Network for Cross-Domain Recommendation. IEEE Trans. Knowl. Data Eng. 35(4): 3266-3278 (2023) - [j190]Anjin Liu, Jie Lu, Yiliao Song, Junyu Xuan, Guangquan Zhang:
Concept Drift Detection Delay Index. IEEE Trans. Knowl. Data Eng. 35(5): 4585-4597 (2023) - [j189]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Dynamic Classifier Alignment for Unsupervised Multi-Source Domain Adaptation. IEEE Trans. Knowl. Data Eng. 35(5): 4727-4740 (2023) - [j188]Ming Zhou, Jie Lu, Yiliao Song, Guangquan Zhang:
Multi-Stream Concept Drift Self-Adaptation Using Graph Neural Network. IEEE Trans. Knowl. Data Eng. 35(12): 12828-12841 (2023) - [j187]Li Zhong, Zhen Fang, Feng Liu, Bo Yuan, Guangquan Zhang, Jie Lu:
Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation. IEEE Trans. Neural Networks Learn. Syst. 34(8): 3859-3873 (2023) - [j186]Yiliao Song, Jie Lu, Haiyan Lu, Guangquan Zhang:
Learning Data Streams With Changing Distributions and Temporal Dependency. IEEE Trans. Neural Networks Learn. Syst. 34(8): 3952-3965 (2023) - [j185]Wenhui Liao, Qian Zhang, Bo Yuan, Guangquan Zhang, Jie Lu:
Heterogeneous Multidomain Recommender System Through Adversarial Learning. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8965-8977 (2023) - [c160]Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang:
An Augmented Learning Approach for Multiple Data Streams Under Concept Drift. AI (1) 2023: 391-402 - [c159]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Attention-Bridging TS Fuzzy Rules for Universal Multi-Domain Adaptation Without Source Data. FUZZ 2023: 1-6 - [c158]Guangzhi Ma, Jie Lu, Guangquan Zhang:
Interval-Valued Observations-Based Multi-Source Domain Adaptation Using Fuzzy Neural Networks. FUZZ 2023: 1-6 - [c157]Mengjia Wu, Yi Zhang, Hua Lin, Mark Grosser, Guangquan Zhang, Jie Lu:
BiblioEngine: An AI-Empowered Platform for Disease Genetic Knowledge Mining. HIS 2023: 187-198 - [c156]Xinheng Wu, Jie Lu, Zhen Fang, Guangquan Zhang:
Meta OOD Learning For Continuously Adaptive OOD Detection. ICCV 2023: 19296-19307 - [c155]Guohang Zeng, Zhen Fang, Guangquan Zhang, Jie Lu:
One-step Domain Adaptation Approach with Partial Label. IJCNN 2023: 1-8 - [c154]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Domain Adaptation for Image Segmentation with Category-Guide Classifier. ISKE 2023: 568-572 - [c153]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Multi-Source Domain Adaptation with Incomplete Source Label Spaces. KES 2023: 2343-2350 - [c152]Pham Minh Thu Do, Qian Zhang, Guangquan Zhang, Jie Lu:
meta-GRS: A Graph Neural Network for Cross-Domain Recommender System via Meta-Learning. KES 2023: 2536-2545 - [c151]Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang:
TCR-M: A Topic Change Recognition-based Method for Data Stream Learning. KES 2023: 3001-3010 - [i28]Xinheng Wu, Jie Lu, Zhen Fang, Guangquan Zhang:
Meta OOD Learning for Continuously Adaptive OOD Detection. CoRR abs/2309.11705 (2023) - [i27]En Yu, Jie Lu, Bin Zhang, Guangquan Zhang:
Online Boosting Adaptive Learning under Concept Drift for Multistream Classification. CoRR abs/2312.10841 (2023) - 2022
- [j184]Bin Wang, Jie Lu, Tianrui Li, Zheng Yan, Guangquan Zhang:
A quantile fusion methodology for deep forecasting. Neurocomputing 483: 286-298 (2022) - [j183]Kun Wang, Jie Lu, Anjin Liu, Yiliao Song, Li Xiong, Guangquan Zhang:
Elastic gradient boosting decision tree with adaptive iterations for concept drift adaptation. Neurocomputing 491: 288-304 (2022) - [j182]En Yu, Yiliao Song, Guangquan Zhang, Jie Lu:
Learn-to-adapt: Concept drift adaptation for hybrid multiple streams. Neurocomputing 496: 121-130 (2022) - [j181]Kai Yang, Jie Lu, Wanggen Wan, Guangquan Zhang, Li Hou:
Transfer learning based on sparse Gaussian process for regression. Inf. Sci. 605: 286-300 (2022) - [j180]Hang Yu, Qingyong Zhang, Tianyu Liu, Jie Lu, Yimin Wen, Guangquan Zhang:
Meta-ADD: A meta-learning based pre-trained model for concept drift active detection. Inf. Sci. 608: 996-1009 (2022) - [j179]Hang Yu, Jie Lu, Guangquan Zhang:
Continuous Support Vector Regression for Nonstationary Streaming Data. IEEE Trans. Cybern. 52(5): 3592-3605 (2022) - [j178]Fan Dong, Jie Lu, Yiliao Song, Feng Liu, Guangquan Zhang:
A Drift Region-Based Data Sample Filtering Method. IEEE Trans. Cybern. 52(9): 9377-9390 (2022) - [j177]Hang Yu, Jie Lu, Guangquan Zhang:
Topology Learning-Based Fuzzy Random Neural Networks for Streaming Data Regression. IEEE Trans. Fuzzy Syst. 30(2): 412-425 (2022) - [j176]Hang Yu, Jie Lu, Anjin Liu, Bin Wang, Ruimin Li, Guangquan Zhang:
Real-Time Prediction System of Train Carriage Load Based on Multi-Stream Fuzzy Learning. IEEE Trans. Intell. Transp. Syst. 23(9): 15155-15165 (2022) - [j175]Hang Yu, Jie Lu, Guangquan Zhang:
An Online Robust Support Vector Regression for Data Streams. IEEE Trans. Knowl. Data Eng. 34(1): 150-163 (2022) - [j174]Yiliao Song, Jie Lu, Anjin Liu, Haiyan Lu, Guangquan Zhang:
A Segment-Based Drift Adaptation Method for Data Streams. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4876-4889 (2022) - [j173]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Multi-Source Contribution Learning for Domain Adaptation. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5293-5307 (2022) - [j172]Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu:
Learning From a Complementary-Label Source Domain: Theory and Algorithms. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7667-7681 (2022) - [j171]Hang Yu, Jie Lu, Guangquan Zhang:
MORStreaming: A Multioutput Regression System for Streaming Data. IEEE Trans. Syst. Man Cybern. Syst. 52(8): 4862-4874 (2022) - [c150]Zhaoqing Liu, Anjin Liu, Guangquan Zhang, Jie Lu:
An Empirical Study of Fuzzy Decision Tree for Gradient Boosting Ensemble. AI 2022: 716-727 - [c149]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Source-Free Multi-Domain Adaptation with Generally Auxiliary Model Training. IJCNN 2022: 1-8 - [i26]Guangzhi Ma, Jie Lu, Feng Liu, Zhen Fang, Guangquan Zhang:
Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms. CoRR abs/2206.04311 (2022) - [i25]Tianyu Liu, Jie Lu, Zheng Yan, Guangquan Zhang:
Streaming PAC-Bayes Gaussian process regression with a performance guarantee for online decision making. CoRR abs/2210.08486 (2022) - 2021
- [j170]Wenjun Chang, Qian Zhang, Chao Fu, Weiyong Liu, Guangquan Zhang, Jie Lu:
A cross-domain recommender system through information transfer for medical diagnosis. Decis. Support Syst. 143: 113489 (2021) - [j169]Tianyu Liu, Jie Lu, Zheng Yan, Guangquan Zhang:
Statistical generalization performance guarantee for meta-learning with data dependent prior. Neurocomputing 465: 391-405 (2021) - [j168]Qian Liu, Jie Lu, Guangquan Zhang, Tao Shen, Zhihan Zhang, Heyan Huang:
Domain-specific meta-embedding with latent semantic structures. Inf. Sci. 555: 410-423 (2021) - [j167]Kai Yang, Jie Lu, Wanggen Wan, Guangquan Zhang:
Multi-source transfer regression via source-target pairwise segment. Inf. Sci. 556: 389-403 (2021) - [j166]Yi Zhang, Mengjia Wu, George Yijun Tian, Guangquan Zhang, Jie Lu:
Ethics and privacy of artificial intelligence: Understandings from bibliometrics. Knowl. Based Syst. 222: 106994 (2021) - [j165]Anjin Liu, Jie Lu, Guangquan Zhang:
Concept Drift Detection via Equal Intensity k-Means Space Partitioning. IEEE Trans. Cybern. 51(6): 3198-3211 (2021) - [j164]Qian Liu, Heyan Huang, Junyu Xuan, Guangquan Zhang, Yang Gao, Jie Lu:
A Fuzzy Word Similarity Measure for Selecting Top-$k$ Similar Words in Query Expansion. IEEE Trans. Fuzzy Syst. 29(8): 2132-2144 (2021) - [j163]Anjin Liu, Jie Lu, Guangquan Zhang:
Concept Drift Detection: Dealing With Missing Values via Fuzzy Distance Estimations. IEEE Trans. Fuzzy Syst. 29(11): 3219-3233 (2021) - [j162]Feng Liu, Guangquan Zhang, Jie Lu:
Multisource Heterogeneous Unsupervised Domain Adaptation via Fuzzy Relation Neural Networks. IEEE Trans. Fuzzy Syst. 29(11): 3308-3322 (2021) - [j161]Junyu Xuan, Jie Lu, Guangquan Zhang:
Bayesian Nonparametric Unsupervised Concept Drift Detection for Data Stream Mining. ACM Trans. Intell. Syst. Technol. 12(1): 5:1-5:22 (2021) - [j160]Anjin Liu, Jie Lu, Guangquan Zhang:
Diverse Instance-Weighting Ensemble Based on Region Drift Disagreement for Concept Drift Adaptation. IEEE Trans. Neural Networks Learn. Syst. 32(1): 293-307 (2021) - [j159]Zhen Fang, Jie Lu, Feng Liu, Junyu Xuan, Guangquan Zhang:
Open Set Domain Adaptation: Theoretical Bound and Algorithm. IEEE Trans. Neural Networks Learn. Syst. 32(10): 4309-4322 (2021) - [c148]Li Zhong, Zhen Fang, Feng Liu, Jie Lu, Bo Yuan, Guangquan Zhang:
How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches? AAAI 2021: 11079-11087 - [c147]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Multi-Source Domain Adaptation with Fuzzy-Rule based Deep Neural Networks. FUZZ-IEEE 2021: 1-6 - [c146]Guangzhi Ma, Feng Liu, Guangquan Zhang, Jie Lu:
Learning from Imprecise Observations: An Estimation Error Bound based on Fuzzy Random Variables. FUZZ-IEEE 2021: 1-8 - [c145]Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang:
Learning Bounds for Open-Set Learning. ICML 2021: 3122-3132 - [c144]Ming Zhou, Yiliao Song, Guangquan Zhang, Bin Zhang, Jie Lu:
An Efficient Bayesian Neural Network for Multiple Data Streams. IJCNN 2021: 1-8 - [i24]Zhong Li, Zhen Fang, Feng Liu, Jie Lu, Bo Yuan, Guangquan Zhang:
How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches? CoRR abs/2101.01104 (2021) - [i23]Tianyu Liu, Jie Lu, Zheng Yan, Guangquan Zhang:
PAC-Bayes Bounds for Meta-learning with Data-Dependent Prior. CoRR abs/2102.03748 (2021) - [i22]Hang Yu, Tianyu Liu, Jie Lu, Guangquan Zhang:
Automatic Learning to Detect Concept Drift. CoRR abs/2105.01419 (2021) - [i21]Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang:
Learning Bounds for Open-Set Learning. CoRR abs/2106.15792 (2021) - [i20]Adi Lin, Jie Lu, Junyu Xuan, Fujin Zhu, Guangquan Zhang:
Deep Bayesian Estimation for Dynamic Treatment Regimes with a Long Follow-up Time. CoRR abs/2109.11929 (2021) - [i19]Junyu Xuan, Jie Lu, Guangquan Zhang:
Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning. CoRR abs/2109.13233 (2021) - 2020
- [b4]Jie Lu, Qian Zhang, Guangquan Zhang:
Recommender Systems - Advanced Developments. Intelligent Information Systems 6, WorldScientific 2020, ISBN 9789811224621, pp. 1-380 - [j158]Yi Zhang, Mengjia Wu, Hua Lin, Steven Tipper, Mark Grosser, Guangquan Zhang, Jie Lu:
Framework of Computational Intelligence-Enhanced Knowledge Base Construction: Methodology and A Case of Gene-Related Cardiovascular Disease. Int. J. Comput. Intell. Syst. 13(1): 1109-1119 (2020) - [j157]Fujin Zhu, Jie Lu, Adi Lin, Guangquan Zhang:
A Pareto-smoothing method for causal inference using generalized Pareto distribution. Neurocomputing 378: 142-152 (2020) - [j156]Guanjin Wang, Guangquan Zhang, Kup-Sze Choi, Kin-Man Lam, Jie Lu:
Output based transfer learning with least squares support vector machine and its application in bladder cancer prognosis. Neurocomputing 387: 279-292 (2020) - [j155]Bin Wang, Tianrui Li, Zheng Yan, Guangquan Zhang, Jie Lu:
DeepPIPE: A distribution-free uncertainty quantification approach for time series forecasting. Neurocomputing 397: 11-19 (2020) - [j154]Guanjin Wang, Jie Lu, Kup-Sze Choi, Guangquan Zhang:
A Transfer-Based Additive LS-SVM Classifier for Handling Missing Data. IEEE Trans. Cybern. 50(2): 739-752 (2020) - [j153]Yiliao Song, Jie Lu, Haiyan Lu, Guangquan Zhang:
Fuzzy Clustering-Based Adaptive Regression for Drifting Data Streams. IEEE Trans. Fuzzy Syst. 28(3): 544-557 (2020) - [j152]Jie Lu, Hua Zuo, Guangquan Zhang:
Fuzzy Multiple-Source Transfer Learning. IEEE Trans. Fuzzy Syst. 28(12): 3418-3431 (2020) - [j151]Adi Lin, Jie Lu, Junyu Xuan, Fujin Zhu, Guangquan Zhang:
A Causal Dirichlet Mixture Model for Causal Inference from Observational Data. ACM Trans. Intell. Syst. Technol. 11(3): 33:1-33:29 (2020) - [j150]Hang Yu, Jie Lu, Guangquan Zhang:
Online Topology Learning by a Gaussian Membership-Based Self-Organizing Incremental Neural Network. IEEE Trans. Neural Networks Learn. Syst. 31(10): 3947-3961 (2020) - [j149]Feng Liu, Guangquan Zhang, Jie Lu:
Heterogeneous Domain Adaptation: An Unsupervised Approach. IEEE Trans. Neural Networks Learn. Syst. 31(12): 5588-5602 (2020) - [j148]Junyu Xuan, Xiangfeng Luo, Jie Lu, Guangquan Zhang:
Web event evolution trend prediction based on its computational social context. World Wide Web 23(3): 1861-1886 (2020) - [c143]Hang Yu, Anjin Liu, Bin Wang, Ruimin Li, Guangquan Zhang, Jie Lu:
Real-Time Decision Making for Train Carriage Load Prediction via Multi-stream Learning. Australasian Conference on Artificial Intelligence 2020: 29-41 - [c142]Kun Wang, Anjin Liu, Jie Lu, Guangquan Zhang, Li Xiong:
An Elastic Gradient Boosting Decision Tree for Concept Drift Learning. Australasian Conference on Artificial Intelligence 2020: 420-432 - [c141]Feng Liu, Guangquan Zhang, Jie Lu:
A Novel Non-parametric Two-Sample Test on Imprecise Observations. FUZZ-IEEE 2020: 1-6 - [c140]Yiliao Song, Guangquan Zhang, Haiyan Lu, Jie Lu:
A Fuzzy Drift Correlation Matrix for Multiple Data Stream Regression. FUZZ-IEEE 2020: 1-6 - [c139]