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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, USA
- affiliation (1979 - 1997): Hebei University, Baoding, China
Other persons with the same name
- Guangquan Zhang 0002 — Soochow University, Suzhou, China
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2020 – today
- 2020
[j154]Fujin Zhu
, Jie Lu, Adi Lin, Guangquan Zhang:
A Pareto-smoothing method for causal inference using generalized Pareto distribution. Neurocomputing 378: 142-152 (2020)- [j153]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) - [j152]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) - [j151]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) - [j150]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) - [j149]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) - [j148]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) - [j147]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) - [c134]Feng Liu, Guangquan Zhang, Jie Lu:
A Novel Non-parametric Two-Sample Test on Imprecise Observations. FUZZ-IEEE 2020: 1-6 - [c133]Yiliao Song, Guangquan Zhang, Haiyan Lu, Jie Lu:
A Fuzzy Drift Correlation Matrix for Multiple Data Stream Regression. FUZZ-IEEE 2020: 1-6 - [c132]Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu:
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation. IJCAI 2020: 2526-2532 - [c131]Qian Zhang, Jie Lu, Guangquan Zhang:
Cross-Domain Recommendation with Multiple Sources. IJCNN 2020: 1-7 - [c130]Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang:
Multi-Source Domain Adaptation with Distribution Fusion and Relationship Extraction. IJCNN 2020: 1-6 - [c129]Anjin Liu, Guangquan Zhang, Kun Wang, Jie Lu:
Fast Switch Naïve Bayes to Avoid Redundant Update for Concept Drift Learning. IJCNN 2020: 1-7 - [c128]Hua Zuo, Jie Lu, Guangquan Zhang:
Multiple-source Domain Adaptation in Rule-based Neural Network. IJCNN 2020: 1-6 - [i18]Feng Liu, Wenkai Xu, Jie Lu, Guangquan Zhang, Arthur Gretton, Dougal J. Sutherland:
Learning Deep Kernels for Non-Parametric Two-Sample Tests. CoRR abs/2002.09116 (2020) - [i17]Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang:
Learning under Concept Drift: A Review. CoRR abs/2004.05785 (2020) - [i16]Anjin Liu, Jie Lu, Guangquan Zhang:
Diverse Instances-Weighting Ensemble based on Region Drift Disagreement for Concept Drift Adaptation. CoRR abs/2004.05810 (2020) - [i15]Anjin Liu, Jie Lu, Guangquan Zhang:
Concept Drift Detection via Equal Intensity k-means Space Partitioning. CoRR abs/2004.11587 (2020) - [i14]Li Zhong, Zhen Fang, Feng Liu, Bo Yuan, Guangquan Zhang, Jie Lu:
Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation. CoRR abs/2006.13022 (2020) - [i13]Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu:
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation. CoRR abs/2007.14612 (2020) - [i12]Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu:
Learning from a Complementary-label Source Domain: Theory and Algorithms. CoRR abs/2008.01454 (2020) - [i11]Anjin Liu, Jie Lu, Guangquan Zhang:
Concept Drift Detection: Dealing with MissingValues via Fuzzy Distance Estimations. CoRR abs/2008.03662 (2020)
2010 – 2019
- 2019
- [j146]Junyu Xuan, Jie Lu, Guangquan Zhang:
Cooperative hierarchical Dirichlet processes: Superposition vs. maximization. Artif. Intell. 271: 43-73 (2019) - [j145]Junyu Xuan, Jie Lu, Guangquan Zhang:
A Survey on Bayesian Nonparametric Learning. ACM Comput. Surv. 52(1): 13:1-13:36 (2019) - [j144]Ximeng Wang, Yun Liu, Jie Lu, Fei Xiong, Guangquan Zhang:
TruGRC: Trust-Aware Group Recommendation with Virtual Coordinators. Future Gener. Comput. Syst. 94: 224-236 (2019) - [j143]Mingsong Mao, Jie Lu, Jialin Han, Guangquan Zhang:
Multiobjective e-commerce recommendations based on hypergraph ranking. Inf. Sci. 471: 269-287 (2019) - [j142]Ruiping Yin, Kan Li, Guangquan Zhang, Jie Lu:
A deeper graph neural network for recommender systems. Knowl. Based Syst. 185 (2019) - [j141]Shan Xue, Jie Lu, Guangquan Zhang:
Cross-domain network representations. Pattern Recognit. 94: 135-148 (2019) - [j140]Peng Hao, Guangquan Zhang, Luis Martínez-López, Jie Lu:
Regularizing Knowledge Transfer in Recommendation With Tag-Inferred Correlation. IEEE Trans. Cybern. 49(1): 83-96 (2019) - [j139]Jie Lu, Zheng Yan, Jialin Han, Guangquan Zhang:
Data-Driven Decision-Making (D3M): Framework, Methodology, and Directions. IEEE Trans. Emerg. Top. Comput. Intell. 3(4): 286-296 (2019) - [j138]Hua Zuo, Jie Lu, Guangquan Zhang, Feng Liu:
Fuzzy Transfer Learning Using an Infinite Gaussian Mixture Model and Active Learning. IEEE Trans. Fuzzy Syst. 27(2): 291-303 (2019) - [j137]Hua Zuo, Jie Lu, Guangquan Zhang, Witold Pedrycz:
Fuzzy Rule-Based Domain Adaptation in Homogeneous and Heterogeneous Spaces. IEEE Trans. Fuzzy Syst. 27(2): 348-361 (2019) - [j136]Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang:
Learning under Concept Drift: A Review. IEEE Trans. Knowl. Data Eng. 31(12): 2346-2363 (2019) - [j135]Qian Zhang, Jie Lu, Dianshuang Wu, Guangquan Zhang:
A Cross-Domain Recommender System With Kernel-Induced Knowledge Transfer for Overlapping Entities. IEEE Trans. Neural Networks Learn. Syst. 30(7): 1998-2012 (2019) - [j134]Wei Wang, Guangquan Zhang, Jie Lu:
Hierarchy Visualization for Group Recommender Systems. IEEE Trans. Syst. Man Cybern. Syst. 49(6): 1152-1163 (2019) - [j133]Guanjin Wang, Guangquan Zhang, Kup-Sze Choi, Jie Lu:
Deep Additive Least Squares Support Vector Machines for Classification With Model Transfer. IEEE Trans. Syst. Man Cybern. Syst. 49(7): 1527-1540 (2019) - [c127]Feng Liu, Guangquan Zhang, Jie Lu:
A Novel Fuzzy Neural Network for Unsupervised Domain Adaptation in Heterogeneous Scenarios. FUZZ-IEEE 2019: 1-6 - [c126]Yiliao Song, Guangquan Zhang, Haiyan Lu, Jie Lu:
A Noise-tolerant Fuzzy c-Means based Drift Adaptation Method for Data Stream Regression. FUZZ-IEEE 2019: 1-6 - [c125]Hua Zuo, Guangquan Zhang, Witold Pedrycz, Jie Lu:
Domain Selection of Transfer Learning in Fuzzy Prediction Models. FUZZ-IEEE 2019: 1-6 - [c124]Adi Lin, Jie Lu, Junyu Xuan, Fujin Zhu, Guangquan Zhang:
One-Stage Deep Instrumental Variable Method for Causal Inference from Observational Data. ICDM 2019: 419-428 - [c123]Hua Zuo, Guangquan Zhang, Jie Lu:
Fuzzy Transfer Learning in Heterogeneous Space Using Takagi-Sugeno Fuzzy Models. IFSA/NAFIPS 2019: 752-763 - [c122]Dennis Chow, Anjin Liu, Guangquan Zhang, Jie Lu:
Knowledge graph-based entity importance learning for multi-stream regression on Australian fuel price forecasting. IJCNN 2019: 1-8 - [c121]Zhen Fang, Jie Lu, Feng Liu, Guangquan Zhang:
Unsupervised Domain Adaptation with Sphere Retracting Transformation. IJCNN 2019: 1-8 - [c120]Ruiping Yin, Kan Li, Jie Lu, Guangquan Zhang:
RsyGAN: Generative Adversarial Network for Recommender Systems. IJCNN 2019: 1-7 - [c119]Hang Yu, Jie Lu, Jialu Xu, Guangquan Zhang:
A Hybrid Incremental Regression Neural Network for Uncertain Data Streams. IJCNN 2019: 1-8 - [c118]Qian Zhang, Peng Hao, Jie Lu, Guangquan Zhang:
Cross-domain Recommendation with Semantic Correlation in Tagging Systems. IJCNN 2019: 1-8 - [c117]Bin Zhang, Jie Lu, Guangquan Zhang:
Drift Adaptation via Joint Distribution Alignment. ISKE 2019: 498-504 - [c116]Qian Zhang, Di Zhang, Jie Lu, Guangquan Zhang, Wei Qu, Mark Cohen:
A Recommender System for Cold-start Items: A Case Study in the Real Estate Industry. ISKE 2019: 1185-1192 - [c115]Yi Zhang, Yihe Zhu, Lu Huang, Guangquan Zhang, Jie Lu:
Characterizing the Potential of Being Emerging Generic Technologies: A Bi-Layer Network Analytics-based Prediction Method. ISSI 2019: 1436-1447 - [c114]Bin Wang, Jie Lu, Zheng Yan, Huaishao Luo, Tianrui Li, Yu Zheng, Guangquan Zhang:
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting. KDD 2019: 2087-2095 - [c113]Ruiping Yin, Kan Li, Jie Lu, Guangquan Zhang:
Enhancing Fashion Recommendation with Visual Compatibility Relationship. WWW 2019: 3434-3440 - [i10]Feng Liu, Jie Lu, Bo Han, Gang Niu, Guangquan Zhang, Masashi Sugiyama:
Butterfly: A Panacea for All Difficulties in Wildly Unsupervised Domain Adaptation. CoRR abs/1905.07720 (2019) - [i9]Zhen Fang, Jie Lu, Feng Liu, Junyu Xuan, Guangquan Zhang:
Open Set Domain Adaptation: Theoretical Bound and Algorithm. CoRR abs/1907.08375 (2019) - [i8]Shan Xue, Jie Lu, Guangquan Zhang:
Cross-domain Network Representations. CoRR abs/1908.00205 (2019) - [i7]Shan Xue, Jie Lu, Guangquan Zhang, Li Xiong:
A Framework of Transferring Structures Across Large-scale Information Networks. CoRR abs/1911.04665 (2019) - 2018
- [j132]Fan Dong, Jie Lu, Guangquan Zhang, Kan Li:
Active Fuzzy Weighting Ensemble for Dealing with Concept Drift. Int. J. Comput. Intell. Syst. 11(1): 438-450 (2018) - [j131]Junyu Xuan, Jie Lu, Zheng Yan, Guangquan Zhang:
Bayesian Deep Reinforcement Learning via Deep Kernel Learning. Int. J. Comput. Intell. Syst. 12(1): 164-171 (2018) - [j130]Yue Zheng, Guangquan Zhang, Zhen Zhang, Jie Lu:
A reducibility method for the weak linear bilevel programming problems and a case study in principal-agent. Inf. Sci. 454-455: 46-58 (2018) - [j129]Yi Zhang, Jie Lu, Feng Liu, Qian Liu, Alan L. Porter, Hongshu Chen, Guangquan Zhang:
Does deep learning help topic extraction? A kernel k-means clustering method with word embedding. J. Informetrics 12(4): 1099-1117 (2018) - [j128]Fan Dong, Guangquan Zhang, Jie Lu, Kan Li:
Fuzzy competence model drift detection for data-driven decision support systems. Knowl. Based Syst. 143: 284-294 (2018) - [j127]Jie Lu, Junyu Xuan, Guangquan Zhang, Xiangfeng Luo:
Structural property-aware multilayer network embedding for latent factor analysis. Pattern Recognit. 76: 228-241 (2018) - [j126]Anjin Liu, Jie Lu, Feng Liu, Guangquan Zhang:
Accumulating regional density dissimilarity for concept drift detection in data streams. Pattern Recognit. 76: 256-272 (2018) - [j125]Hua Zuo, Guangquan Zhang, Witold Pedrycz, Vahid Behbood, Jie Lu:
Granular Fuzzy Regression Domain Adaptation in Takagi-Sugeno Fuzzy Models. IEEE Trans. Fuzzy Syst. 26(2): 847-858 (2018) - [j124]Feng Liu, Jie Lu, Guangquan Zhang:
Unsupervised Heterogeneous Domain Adaptation via Shared Fuzzy Equivalence Relations. IEEE Trans. Fuzzy Syst. 26(6): 3555-3568 (2018) - [j123]Tinghua Wang, Jie Lu, Guangquan Zhang:
Two-Stage Fuzzy Multiple Kernel Learning Based on Hilbert-Schmidt Independence Criterion. IEEE Trans. Fuzzy Syst. 26(6): 3703-3714 (2018) - [j122]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes. IEEE Trans. Neural Networks Learn. Syst. 29(5): 1835-1849 (2018) - [j121]Jorge Castro, Jie Lu, Guangquan Zhang, Yucheng Dong, Luis Martínez-López:
Opinion Dynamics-Based Group Recommender Systems. IEEE Trans. Syst. Man Cybern. Syst. 48(12): 2394-2406 (2018) - [c112]Qian Liu, Heyan Huang, Guangquan Zhang, Yang Gao, Junyu Xuan, Jie Lu:
Semantic Structure-Based Word Embedding by Incorporating Concept Convergence and Word Divergence. AAAI 2018: 5261-5268 - [c111]Zheng Yan, Jie Lu, Guangquan Zhang:
Distributed Model Predictive Control of Linear Systems with Coupled Constraints Based on Collective Neurodynamic Optimization. Australasian Conference on Artificial Intelligence 2018: 318-328 - [c110]Fujin Zhu, Adi Lin, Guangquan Zhang, Jie Lu:
Counterfactual Inference with Hidden Confounders Using Implicit Generative Models. Australasian Conference on Artificial Intelligence 2018: 519-530 - [c109]Feng Liu, Guangquan Zhang, Jie Lu:
Unconstrained fuzzy feature fusion for heterogeneous unsupervised domain adaptation. FUZZ-IEEE 2018: 1-8 - [c108]Yiliao Song, Guangquan Zhang, Haiyan Lu, Jie Lu:
A Self-adaptive Fuzzy Network for Prediction in Non-stationary Environments. FUZZ-IEEE 2018: 1-8 - [c107]Hang Yu, Jie Lu, Guangquan Zhang, Dianshuang Wu:
A Dual Neural Network Based On Confidence Intervals For Fuzzy Random Regression Problems. FUZZ-IEEE 2018: 1-8 - [c106]Bin Wang, Zheng Yan, Jie Lu, Guangquan Zhang, Tianrui Li:
Deep Multi-task Learning for Air Quality Prediction. ICONIP (5) 2018: 93-103 - [c105]Qian Zhang, Dianshuang Wu, Jie Lu, Guangquan Zhang:
Cross-domain Recommendation with Probabilistic Knowledge Transfer. ICONIP (3) 2018: 208-219 - [c104]Hua Zuo, Guangquan Zhang, Jie Lu:
Fuzzy Domain Adaptation Using Unlabeled Target Data. ICONIP (3) 2018: 242-250 - [c103]Bin Wang, Zheng Yan, Jie Lu, Guangquan Zhang, Tianrui Li:
Explore Uncertainty in Residual Networks for Crowds Flow Prediction. IJCNN 2018: 1-7 - [c102]Shan Xue, Jie Lu, Guangquan Zhang, Li Xiong:
A Framework of Transferring Structures Across Large-scale Information Networks. IJCNN 2018: 1-6 - [c101]Hang Yu, Jie Lu, Guangquan Zhang:
An Incremental Dual nu-Support Vector Regression Algorithm. PAKDD (2) 2018: 522-533 - [c100]Qian Zhang, Jie Lu, Dianshuang Wu, Guangquan Zhang:
Cross-domain Recommendation with Consistent Knowledge Transfer by Subspace Alignment. WISE (2) 2018: 67-82 - [i6]Bin Wang, Zheng Yan, Huaishao Luo, Tianrui Li, Jie Lu, Guangquan Zhang:
Deep Uncertainty Learning: A Machine Learning Approach for Weather Forecasting. CoRR abs/1812.09467 (2018) - 2017
- [j120]Ximeng Wang, Yun Liu, Guangquan Zhang, Yi Zhang, Hongshu Chen, Jie Lu:
Mixed Similarity Diffusion for Recommendation on Bipartite Networks. IEEE Access 5: 21029-21038 (2017) - [j119]Qian Zhang, Dianshuang Wu, Jie Lu, Feng Liu, Guangquan Zhang:
A cross-domain recommender system with consistent information transfer. Decis. Support Syst. 104: 49-63 (2017) - [j118]Junyu Xuan, Xiangfeng Luo, Jie Lu, Guangquan Zhang:
Explicitly and implicitly exploiting the hierarchical structure for mining website interests on news events. Inf. Sci. 420: 263-277 (2017) - [j117]Jialin Han, Jie Lu, Guangquan Zhang:
Tri-level decision-making for decentralized vendor-managed inventory. Inf. Sci. 421: 85-103 (2017) - [j116]Yi Zhang, Guangquan Zhang, Donghua Zhu, Jie Lu:
Scientific evolutionary pathways: Identifying and visualizing relationships for scientific topics. J. Assoc. Inf. Sci. Technol. 68(8): 1925-1939 (2017) - [j115]Yi Zhang, Hongshu Chen, Jie Lu, Guangquan Zhang:
Detecting and predicting the topic change of Knowledge-based Systems: A topic-based bibliometric analysis from 1991 to 2016. Knowl. Based Syst. 133: 255-268 (2017) - [j114]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
A Bayesian nonparametric model for multi-label learning. Mach. Learn. 106(11): 1787-1815 (2017) - [j113]Yi Zhang, Yue Qian, Ying Huang, Ying Guo, Guangquan Zhang, Jie Lu:
An entropy-based indicator system for measuring the potential of patents in technological innovation: rejecting moderation. Scientometrics 111(3): 1925-1946 (2017) - [j112]Chao Yang, Donghua Zhu, Xuefeng Wang, Yi Zhang, Guangquan Zhang, Jie Lu:
Requirement-oriented core technological components' identification based on SAO analysis. Scientometrics 112(3): 1229-1248 (2017) - [j111]Mahardhika Pratama, Guangquan Zhang, Meng Joo Er, Sreenatha G. Anavatti:
An Incremental Type-2 Meta-Cognitive Extreme Learning Machine. IEEE Trans. Cybern. 47(2): 339-353 (2017) - [j110]Mingsong Mao, Jie Lu, Guangquan Zhang, Jinlong Zhang:
Multirelational Social Recommendations via Multigraph Ranking. IEEE Trans. Cybern. 47(12): 4049-4061 (2017) - [j109]Mahardhika Pratama, Jie Lu, Edwin Lughofer, Guangquan Zhang, Meng Joo Er:
An Incremental Learning of Concept Drifts Using Evolving Type-2 Recurrent Fuzzy Neural Networks. IEEE Trans. Fuzzy Syst. 25(5): 1175-1192 (2017) - [j108]Jie Lu, Francisco Herrera, Guangquan Zhang:
Guest Editorial Special Section on Fuzzy Systems in Data Science. IEEE Trans. Fuzzy Syst. 25(6): 1373-1375 (2017) - [j107]Hua Zuo, Guangquan Zhang, Witold Pedrycz, Vahid Behbood, Jie Lu:
Fuzzy Regression Transfer Learning in Takagi-Sugeno Fuzzy Models. IEEE Trans. Fuzzy Syst. 25(6): 1795-1807 (2017) - [j106]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
Bayesian Nonparametric Relational Topic Model through Dependent Gamma Processes. IEEE Trans. Knowl. Data Eng. 29(7): 1357-1369 (2017) - [c99]Qian Liu, Heyan Huang, Jie Lu, Yang Gao, Guangquan Zhang:
Enhanced word embedding similarity measures using fuzzy rules for query expansion. FUZZ-IEEE 2017: 1-6 - [c98]Feng Liu, Guangquan Zhang, Jie Lu:
Heterogeneous unsupervised domain adaptation based on fuzzy feature fusion. FUZZ-IEEE 2017: 1-6 - [c97]Anjin Liu, Guangquan Zhang, Jie Lu:
Fuzzy time windowing for gradual concept drift adaptation. FUZZ-IEEE 2017: 1-6 - [c96]Yiliao Song, Guangquan Zhang, Jie Lu, Haiyan Lu:
A fuzzy kernel c-means clustering model for handling concept drift in regression. FUZZ-IEEE 2017: 1-6 - [c95]Ruiping Yin, Kan Li, Guangquan Zhang, Jie Lu:
Detecting overlapping protein complexes in dynamic protein-protein interaction networks by developing a fuzzy clustering algorithm. FUZZ-IEEE 2017: 1-6 - [c94]Hua Zuo, Guangquan Zhang, Jie Lu, Witold Pedrycz:
Fuzzy rule-based transfer learning for label space adaptation. FUZZ-IEEE 2017: 1-6 - [c93]Anjin Liu, Yiliao Song, Guangquan Zhang, Jie Lu:
Regional Concept Drift Detection and Density Synchronized Drift Adaptation. IJCAI 2017: 2280-2286 - [c92]Guanjin Wang, Guangquan Zhang, Kup-Sze Choi, Kin-Man Lam, Jie Lu:
An output-based knowledge transfer approach and its application in bladder cancer prediction. IJCNN 2017: 356-363 - [c91]Fujin Zhu, Guangquan Zhang, Jie Lu, Donghua Zhu:
First-order causal process for causal modelling with instantaneous and cross-temporal relations. IJCNN 2017: 380-387 - [c90]Fan Dong, Jie Lu, Kan Li, Guangquan Zhang:
Concept drift region identification via competence-based discrepancy distribution estimation. ISKE 2017: 1-7 - [c89]Jialin Han, Shuping Wan, Jie Lu, Guangquan Zhang:
Tri-level multi-follower decision-making in a partial-cooperative situation. ISKE 2017: 1-6 - [c88]Dan Shang, Guangquan Zhang, Jie Lu:
Fast concept drift detection using singular vector decomposition. ISKE 2017: 1-6 - [c87]Hang Yu, Jie Lu, Guangquan Zhang:
Learning a fuzzy decision tree from uncertain data. ISKE 2017: 1-7 - [i5]Feng Liu, Guangquan Zhang, Haiyan Lu, Jie Lu:
Heterogeneous Unsupervised Cross-domain Transfer Learning. CoRR abs/1701.02511 (2017) - [i4]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu:
Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization. CoRR abs/1707.05420 (2017) - 2016
- [j105]Ning Lu, Jie Lu, Guangquan Zhang, Ramón López de Mántaras:
A concept drift-tolerant case-base editing technique. Artif. Intell. 230: 108-133 (2016) - [j104]Wei Wang, Guangquan Zhang, Jie Lu:
Member contribution-based group recommender system. Decis. Support Syst. 87: 80-93 (2016) - [j103]Guangquan Zhang, Jialin Han, Jie Lu:
Fuzzy Bi-level Decision-Making Techniques: A Survey. Int. J. Comput. Intell. Syst. 9(sup1): 25-34 (2016) - [j102]Mahardhika Pratama, Jie Lu, Edwin Lughofer, Guangquan Zhang, Sreenatha G. Anavatti:
Scaffolding type-2 classifier for incremental learning under concept drifts. Neurocomputing 191: 304-329 (2016) - [j101]Jie Lu, Jialin Han, Yaoguang Hu, Guangquan Zhang:
Multilevel decision-making: A survey. Inf. Sci. 346-347: 463-487 (2016) - [j100]Jialin Han, Guangquan Zhang, Yaoguang Hu, Jie Lu:
A solution to bi/tri-level programming problems using particle swarm optimization. Inf. Sci. 370-371: 519-537 (2016) - [j99]Yue Zheng, Guangquan Zhang, Jialin Han, Jie Lu:
Pessimistic bilevel optimization model for risk-averse production-distribution planning. Inf. Sci. 372: 677-689 (2016) - [j98]Yi Zhang, Lining Shang, Lu Huang, Alan L. Porter, Guangquan Zhang, Jie Lu, Donghua Zhu:
A hybrid similarity measure method for patent portfolio analysis. J. Informetrics 10(4): 1108-1130 (2016) - [j97]Mohsen Naderpour, Jie Lu, Guangquan Zhang:
A safety-critical decision support system evaluation using situation awareness and workload measures. Reliab. Eng. Syst. Saf. 150: 147-159 (2016) - [j96]Mahardhika Pratama, Jie Lu, Guangquan Zhang:
Evolving Type-2 Fuzzy Classifier. IEEE Trans. Fuzzy Syst. 24(3): 574-589 (2016) - [j95]Xiangfeng Luo, Junyu Xuan, Jie Lu, Guangquan Zhang:
Measuring the Semantic Uncertainty of News Events for Evolution Potential Estimation. ACM Trans. Inf. Syst. 34(4): 24:1-24:25 (2016) - [j94]Junyu Xuan, Xiangfeng Luo, Guangquan Zhang, Jie Lu, Zheng Xu:
Uncertainty Analysis for the Keyword System of Web Events. IEEE Trans. Syst. Man Cybern. Syst. 46(6): 829-842 (2016) - [c86]Anjin Liu, Guangquan Zhang, Jie Lu, Ning Lu, Chin-Teng Lin:
An Online Competence-Based Concept Drift Detection Algorithm. Australasian Conference on Artificial Intelligence 2016: 416-428 - [c85]Tiefeng Zhang, Mingdi Gu, Guangquan Zhang, Jie Lu:
A fast load pattern extraction approach based on dimension reduction and sampling. FUZZ-IEEE 2016: 1253-1258 - [c84]