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ORCIDChengqi Zhang
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- affiliation: University of Technology Sydney, Centre for Artificial Intelligence, FEIT, Ultimo, NSW, Australia
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2020 – today
- 2024
[j149]Chuanhou Sun, Xiaoqiang Ren, Xiangjun Dong, Ping Qiu, Xiaoming Wu, Long Zhao
, Ying Guo, Yongshun Gong, Chengqi Zhang:
Mining actionable repetitive positive and negative sequential patterns. Knowl. Based Syst. 302: 112398 (2024)- [j148]Yejiang Wang, Yuhai Zhao, Zhengkui Wang, Chengqi Zhang, Xingwei Wang:
Robust Multi-Graph Multi-Label Learning With Dual-Granularity Labeling. IEEE Trans. Pattern Anal. Mach. Intell. 46(10): 6509-6524 (2024) - [j147]Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang, Chengqi Zhang:
Transductive Reward Inference on Graph. IEEE Trans. Knowl. Data Eng. 36(11): 7217-7228 (2024) - [c242]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning. IJCAI 2024: 3908-3916 - [c241]Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang:
Federated Prompt Learning for Weather Foundation Models on Devices. IJCAI 2024: 5772-5780 - [c240]Chengpei Xu, Hao Fu, Long Ma, Wenjing Jia, Chengqi Zhang, Feng Xia, Xiaoyu Ai, Binghao Li, Wenjie Zhang:
Seeing Text in the Dark: Algorithm and Benchmark. ACM Multimedia 2024: 2870-2878 - [c239]Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang:
Multivariate Traffic Demand Prediction via 2D Spectral Learning and Global Spatial Optimization. ECML/PKDD (2) 2024: 72-88 - [c238]Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang:
Test-Time Training for Spatial-Temporal Forecasting. SDM 2024: 463-471 - [i61]Hongzhi Yin, Liang Qu, Tong Chen, Wei Yuan, Ruiqi Zheng, Jing Long, Xin Xia, Yuhui Shi, Chengqi Zhang:
On-Device Recommender Systems: A Comprehensive Survey. CoRR abs/2401.11441 (2024) - [i60]Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang, Chengqi Zhang:
Transductive Reward Inference on Graph. CoRR abs/2402.03661 (2024) - [i59]Chengpei Xu, Hao Fu, Long Ma, Wenjing Jia, Chengqi Zhang, Feng Xia, Xiaoyu Ai, Binghao Li, Wenjie Zhang:
Seeing Text in the Dark: Algorithm and Benchmark. CoRR abs/2404.08965 (2024) - [i58]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning. CoRR abs/2404.10942 (2024) - [i57]Renqiang Luo, Tao Tang, Feng Xia, Jiaying Liu, Chengpei Xu, Leo Yu Zhang, Wei Xiang, Chengqi Zhang:
Algorithmic Fairness: A Tolerance Perspective. CoRR abs/2405.09543 (2024) - [i56]He Zhang, Bang Wu, Xiangwen Yang, Xingliang Yuan, Chengqi Zhang, Shirui Pan:
Gradient Transformation: Towards Efficient and Model-Agnostic Unlearning for Dynamic Graph Neural Networks. CoRR abs/2405.14407 (2024) - [i55]Shutong Chen, Tianyi Zhou, Guodong Long, Jie Ma, Jing Jiang, Chengqi Zhang:
Multi-Level Additive Modeling for Structured Non-IID Federated Learning. CoRR abs/2405.16472 (2024) - [i54]Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, Shirui Pan:
ARC: A Generalist Graph Anomaly Detector with In-Context Learning. CoRR abs/2405.16771 (2024) - [i53]Shengchao Chen, Guodong Long, Jing Jiang, Chengqi Zhang:
Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models. CoRR abs/2405.20348 (2024) - [i52]Zicheng Zhao, Linhao Luo, Shirui Pan, Chengqi Zhang, Chen Gong:
Graph Stochastic Neural Process for Inductive Few-shot Knowledge Graph Completion. CoRR abs/2408.01784 (2024) - [i51]Zhiwei Li, Guodong Long, Tianyi Zhou, Jing Jiang, Chengqi Zhang:
Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach. CoRR abs/2408.08931 (2024) - [i50]Yue Tan, Guodong Long, Jing Jiang, Chengqi Zhang:
Influence-oriented Personalized Federated Learning. CoRR abs/2410.03315 (2024) - [i49]Siyu Zhou, Tianyi Zhou, Yijun Yang, Guodong Long, Deheng Ye, Jing Jiang, Chengqi Zhang:
WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents. CoRR abs/2410.07484 (2024) - [i48]Zhiwei Li, Guodong Long, Jing Jiang, Chengqi Zhang:
Personalized Item Representations in Federated Multimodal Recommendation. CoRR abs/2410.08478 (2024) - [i47]Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han:
Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. CoRR abs/2410.12474 (2024) - 2023
- [j146]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Gangyan Xu, Chengqi Zhang:
Shared dynamics learning for large-scale traveling salesman problem. Adv. Eng. Informatics 56: 102005 (2023) - [j145]Xu Zhang, Yongshun Gong, Chengqi Zhang, Xiaoming Wu, Ying Guo, Wenpeng Lu, Long Zhao, Xiangjun Dong:
Spatio-temporal fusion and contrastive learning for urban flow prediction. Knowl. Based Syst. 282: 111104 (2023) - [j144]Yingqing Su, Qi Feng, Wei Liu, Meng Zhu, Honghua Xia, Xiaohong Ma, Wenju Cheng, Jutao Zhang, Chengqi Zhang, Linshan Yang, Xinwei Yin:
Improved Understanding of Trade-Offs and Synergies in Ecosystem Services via Fine Land-Use Classification and Multi-Scale Analysis in the Arid Region of Northwest China. Remote. Sens. 15(20): 4976 (2023) - [j143]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Beyond Low-Pass Filtering: Graph Convolutional Networks With Automatic Filtering. IEEE Trans. Knowl. Data Eng. 35(7): 6687-6697 (2023) - [j142]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
Causal Reinforcement Learning: A Survey. Trans. Mach. Learn. Res. 2023 (2023) - [j141]Ping Qiu, Yongshun Gong, Yuhai Zhao, Longbing Cao, Chengqi Zhang, Xiangjun Dong:
An Efficient Method for Modeling Nonoccurring Behaviors by Negative Sequential Patterns With Loose Constraints. IEEE Trans. Neural Networks Learn. Syst. 34(4): 1864-1878 (2023) - [j140]Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang:
Bidirectional Spatial-Temporal Adaptive Transformer for Urban Traffic Flow Forecasting. IEEE Trans. Neural Networks Learn. Syst. 34(10): 6913-6925 (2023) - [c237]Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang:
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing. AAAI 2023: 9953-9961 - [c236]Xiuying Chen, Guodong Long, Chongyang Tao, Mingzhe Li, Xin Gao, Chengqi Zhang, Xiangliang Zhang:
Improving the Robustness of Summarization Systems with Dual Augmentation. ACL (1) 2023: 6846-6857 - [c235]Xu Zhang, Yongshun Gong, Xinxin Zhang, Xiaoming Wu, Chengqi Zhang, Xiangjun Dong:
Mask- and Contrast-Enhanced Spatio-Temporal Learning for Urban Flow Prediction. CIKM 2023: 3298-3307 - [c234]Wei Wu, Bin Li, Ling Chen, Junbin Gao, Chengqi Zhang:
A Review for Weighted MinHash Algorithms (Extended abstract). ICDE 2023: 3785-3786 - [c233]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Does Continual Learning Equally Forget All Parameters? ICML 2023: 42280-42303 - [c232]Chunxu Zhang, Guodong Long, Tianyi Zhou, Peng Yan, Zijian Zhang, Chengqi Zhang, Bo Yang:
Dual Personalization on Federated Recommendation. IJCAI 2023: 4558-4566 - [c231]Jie Ma, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Structured Federated Learning through Clustered Additive Modeling. NeurIPS 2023 - [c230]Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang:
RiskContra: A Contrastive Approach to Forecast Traffic Risks with Multi-Kernel Networks. PAKDD (4) 2023: 263-275 - [c229]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks. ECML/PKDD (2) 2023: 52-68 - [i46]Chunxu Zhang, Guodong Long, Tianyi Zhou, Peng Yan, Zijian Zhang, Chengqi Zhang, Bo Yang:
Dual Personalization on Federated Recommendation. CoRR abs/2301.08143 (2023) - [i45]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks. CoRR abs/2301.11560 (2023) - [i44]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Does Continual Learning Equally Forget All Parameters? CoRR abs/2304.04158 (2023) - [i43]Xiuying Chen, Guodong Long, Chongyang Tao, Mingzhe Li, Xin Gao, Chengqi Zhang, Xiangliang Zhang:
Improving the Robustness of Summarization Systems with Dual Augmentation. CoRR abs/2306.01090 (2023) - [i42]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
Causal Reinforcement Learning: A Survey. CoRR abs/2307.01452 (2023) - [i41]Shengchao Chen, Guodong Long, Jing Jiang, Dikai Liu, Chengqi Zhang:
Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey. CoRR abs/2312.03014 (2023) - 2022
- [j139]Chun Wang, Shirui Pan, Celina Ping Yu, Ruiqi Hu, Guodong Long, Chengqi Zhang:
Deep neighbor-aware embedding for node clustering in attributed graphs. Pattern Recognit. 122: 108230 (2022) - [j138]Wenli Zhang, Wei Zhang, Yubing Liu, Jutao Zhang, Linshan Yang, Zengru Wang, Zhongchao Mao, Shi Qi, Chengqi Zhang, Zhenliang Yin:
The Role of Soil Salinization in Shaping the Spatio-Temporal Patterns of Soil Organic Carbon Stock. Remote. Sens. 14(13): 3204 (2022) - [j137]Yunqiu Xu, Meng Fang, Ling Chen, Gangyan Xu, Yali Du, Chengqi Zhang:
Reinforcement Learning With Multiple Relational Attention for Solving Vehicle Routing Problems. IEEE Trans. Cybern. 52(10): 11107-11120 (2022) - [j136]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy. IEEE Trans. Knowl. Data Eng. 34(5): 2293-2305 (2022) - [j135]Wei Wu, Bin Li, Ling Chen, Junbin Gao, Chengqi Zhang:
A Review for Weighted MinHash Algorithms. IEEE Trans. Knowl. Data Eng. 34(6): 2553-2573 (2022) - [j134]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Extracting Local Reasoning Chains of Deep Neural Networks. Trans. Mach. Learn. Res. 2022 (2022) - [c228]Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Qinghua Lu, Jing Jiang, Chengqi Zhang:
FedProto: Federated Prototype Learning across Heterogeneous Clients. AAAI 2022: 8432-8440 - [c227]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang:
Perceiving the World: Question-guided Reinforcement Learning for Text-based Games. ACL (1) 2022: 538-560 - [c226]Ming Xie, Jie Ma, Guodong Long, Chengqi Zhang:
Robust Clustered Federated Learning with Bootstrap Median-of-Means. APWeb/WAIM (1) 2022: 237-250 - [c225]Shuang Ao, Tianyi Zhou, Jing Jiang, Guodong Long, Xuan Song, Chengqi Zhang:
EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning. ICML 2022: 822-843 - [c224]Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang:
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection. IJCNN 2022: 1-8 - [i40]Jie Ma, Guodong Long, Tianyi Zhou, Jing Jiang, Chengqi Zhang:
On the Convergence of Clustered Federated Learning. CoRR abs/2202.06187 (2022) - [i39]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang:
Perceiving the World: Question-guided Reinforcement Learning for Text-based Games. CoRR abs/2204.09597 (2022) - [i38]Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang:
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection. CoRR abs/2205.14676 (2022) - [i37]Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang:
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing. CoRR abs/2211.13009 (2022) - 2021
- [j133]Xiaochun Cheng, Chengqi Zhang, Yi Qian, Moayad Aloqaily, Yang Xiao:
Editorial: deep learning for 5G IoT systems. Int. J. Mach. Learn. Cybern. 12(11): 3049-3051 (2021) - [j132]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Search Efficient Binary Network Embedding. ACM Trans. Knowl. Discov. Data 15(4): 61:1-61:27 (2021) - [j131]Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu:
A Comprehensive Survey on Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 32(1): 4-24 (2021) - [c223]Shaoshen Wang, Ling Chen, Farookh Khadeer Hussain, Chengqi Zhang:
Semi-supervised Variational Multi-view Anomaly Detection. APWeb/WAIM (1) 2021: 125-133 - [c222]Hongxin Wu, Chengqi Zhang:
Influence Between Music Based on Big Data Analysis. CIS 2021: 338-342 - [c221]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Chengqi Zhang:
Generalization in Text-based Games via Hierarchical Reinforcement Learning. EMNLP (Findings) 2021: 1343-1353 - [c220]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang:
Isometric Propagation Network for Generalized Zero-shot Learning. ICLR 2021 - [c219]Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang:
Cross-aligned and Gumbel-refactored Autoencoders for Multi-view Anomaly Detection. ICTAI 2021: 1368-1375 - [c218]Yuhai Zhao, Yejiang Wang, Zhengkui Wang, Chengqi Zhang:
Multi-graph Multi-label Learning with Dual-granularity Labeling. KDD 2021: 2327-2337 - [i36]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang:
Isometric Propagation Network for Generalized Zero-shot Learning. CoRR abs/2102.02038 (2021) - [i35]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filtering. CoRR abs/2107.04755 (2021) - [i34]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Zhendong Niu, Chengqi Zhang:
MIMO: Mutual Integration of Patient Journey and Medical Ontology for Healthcare Representation Learning. CoRR abs/2107.09288 (2021) - [i33]Guodong Long, Yue Tan, Jing Jiang, Chengqi Zhang:
Federated Learning for Open Banking. CoRR abs/2108.10749 (2021) - [i32]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Chengqi Zhang:
Generalization in Text-based Games via Hierarchical Reinforcement Learning. CoRR abs/2109.09968 (2021) - 2020
- [j130]Cheng Zheng, Qin Zhang, Guodong Long, Chengqi Zhang, Sean D. Young, Wei Wang:
Measuring Time-Sensitive and Topic-Specific Influence in Social Networks With LSTM and Self-Attention. IEEE Access 8: 82481-82492 (2020) - [j129]Qingfeng Chen, Yulu Qiao, Fang Hu, Yongjie Li, Kai Tan, Mingrui Zhu, Chengqi Zhang:
Community detection in complex network based on APT method. Pattern Recognit. Lett. 138: 193-200 (2020) - [j128]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Network Representation Learning: A Survey. IEEE Trans. Big Data 6(1): 3-28 (2020) - [j127]Shirui Pan, Ruiqi Hu, Sai-Fu Fung, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning Graph Embedding With Adversarial Training Methods. IEEE Trans. Cybern. 50(6): 2475-2487 (2020) - [j126]Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Qinfeng Shi, Chengqi Zhang:
Fast and Low Memory Cost Matrix Factorization: Algorithm, Analysis, and Case Study. IEEE Trans. Knowl. Data Eng. 32(2): 288-301 (2020) - [j125]Haishuai Wang, Jia Wu, Xingquan Zhu, Yixin Chen, Chengqi Zhang:
Time-Variant Graph Classification. IEEE Trans. Syst. Man Cybern. Syst. 50(8): 2883-2896 (2020) - [j124]Fei Xiong, Ximeng Wang, Shirui Pan, Hong Yang, Haishuai Wang, Chengqi Zhang:
Social Recommendation With Evolutionary Opinion Dynamics. IEEE Trans. Syst. Man Cybern. Syst. 50(10): 3804-3816 (2020) - [c217]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Attribute Propagation Network for Graph Zero-Shot Learning. AAAI 2020: 4868-4875 - [c216]Han Zheng, Jing Jiang, Pengfei Wei, Guodong Long, Chengqi Zhang:
Competitive and Cooperative Heterogeneous Deep Reinforcement Learning. AAMAS 2020: 1656-1664 - [c215]Yunqiu Xu, Ling Chen, Meng Fang, Yang Wang, Chengqi Zhang:
Deep Reinforcement Learning with Transformers for Text Adventure Games. CoG 2020: 65-72 - [c214]Hao Huang, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang:
RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. COLING 2020: 556-567 - [c213]Yang Li, Tao Shen, Guodong Long, Jing Jiang, Tianyi Zhou, Chengqi Zhang:
Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention. COLING 2020: 1653-1664 - [c212]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, Chengqi Zhang:
BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes. ICDM 2020: 412-421 - [c211]Tao Shen, Xiubo Geng, Guodong Long, Jing Jiang, Chengqi Zhang, Daxin Jiang:
Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering. IJCAI 2020: 2227-2233 - [c210]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang:
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. KDD 2020: 753-763 - [c209]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang:
Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games. NeurIPS 2020 - [c208]Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu, Chengqi Zhang:
Cooperative Heterogeneous Deep Reinforcement Learning. NeurIPS 2020 - [p5]Guodong Long, Yue Tan, Jing Jiang, Chengqi Zhang:
Federated Learning for Open Banking. Federated Learning 2020: 240-254 - [i31]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang:
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. CoRR abs/2005.11650 (2020) - [i30]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy. CoRR abs/2006.15479 (2020) - [i29]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Attribute Propagation Network for Graph Zero-shot Learning. CoRR abs/2009.11816 (2020) - [i28]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, Chengqi Zhang:
BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes. CoRR abs/2009.13252 (2020) - [i27]Yang Li, Tao Shen, Guodong Long, Jing Jiang, Tianyi Zhou, Chengqi Zhang:
Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention. CoRR abs/2010.03773 (2020) - [i26]Hao Huang, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang:
RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. CoRR abs/2010.04863 (2020) - [i25]Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang:
Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games. CoRR abs/2010.11655 (2020) - [i24]Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu, Chengqi Zhang:
Cooperative Heterogeneous Deep Reinforcement Learning. CoRR abs/2011.00791 (2020) - [i23]Yejiang Wang, Yuhai Zhao, Zhengkui Wang, Chengqi Zhang:
Towards Coarse and Fine-grained Multi-Graph Multi-Label Learning. CoRR abs/2012.10650 (2020)
2010 – 2019
- 2019
- [j123]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Attributed network embedding via subspace discovery. Data Min. Knowl. Discov. 33(6): 1953-1980 (2019) - [j122]Xianwen Jin, Xianling Liu, Yuejiao Hou, Gesheng Song, Chengqi Zhang:
Preliminary Application of Intravoxel Incoherent Motion Diffusion-Weighted Imaging in Diagnosing Lung Cancer. J. Medical Imaging Health Informatics 9(4): 776-780 (2019) - [j121]Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, Chengqi Zhang:
Salient Subsequence Learning for Time Series Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 41(9): 2193-2207 (2019) - [j120]Xinxin Jiang, Shirui Pan, Guodong Long, Fei Xiong, Jing Jiang, Chengqi Zhang:
Cost-Sensitive Parallel Learning Framework for Insurance Intelligence Operation. IEEE Trans. Ind. Electron. 66(12): 9713-9723 (2019) - [j119]Jiangchao Yao, Jiajie Wang, Ivor W. Tsang, Ya Zhang, Jun Sun, Chengqi Zhang, Rui Zhang:
Deep Learning From Noisy Image Labels With Quality Embedding. IEEE Trans. Image Process. 28(4): 1909-1922 (2019) - [j118]Ting Guo, Shirui Pan, Xingquan Zhu, Chengqi Zhang:
CFOND: Consensus Factorization for Co-Clustering Networked Data. IEEE Trans. Knowl. Data Eng. 31(4): 706-719 (2019) - [j117]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang, Philip S. Yu:
Improved Consistent Weighted Sampling Revisited. IEEE Trans. Knowl. Data Eng. 31(12): 2332-2345 (2019) - [c207]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Graph WaveNet for Deep Spatial-Temporal Graph Modeling. IJCAI 2019: 1907-1913 - [c206]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang:
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph. IJCAI 2019: 3015-3022 - [c205]Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang:
Attributed Graph Clustering: A Deep Attentional Embedding Approach. IJCAI 2019: 3670-3676 - [c204]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Tensorized Self-Attention: Efficiently Modeling Pairwise and Global Dependencies Together. NAACL-HLT (1) 2019: 1256-1266 - [c203]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning to Propagate for Graph Meta-Learning. NeurIPS 2019: 1037-1048 - [i22]Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu:
A Comprehensive Survey on Graph Neural Networks. CoRR abs/1901.00596 (2019) - [i21]Shirui Pan, Ruiqi Hu, Sai-Fu Fung, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning Graph Embedding with Adversarial Training Methods. CoRR abs/1901.01250 (2019) - [i20]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Attributed Network Embedding via Subspace Discovery. CoRR abs/1901.04095 (2019) - [i19]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Search Efficient Binary Network Embedding. CoRR abs/1901.04097 (2019) - [i18]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang:
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph. CoRR abs/1905.04042 (2019) - [i17]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Graph WaveNet for Deep Spatial-Temporal Graph Modeling. CoRR abs/1906.00121 (2019) - [i16]Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang:
Attributed Graph Clustering: A Deep Attentional Embedding Approach. CoRR abs/1906.06532 (2019) - [i15]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning to Propagate for Graph Meta-Learning. CoRR abs/1909.05024 (2019) - 2018
- [j116]Jia Wu, Shirui Pan, Chuan Zhou, Gang Li, Wu He, Chengqi Zhang:
Advances in Processing, Mining, and Learning Complex Data: From Foundations to Real-World Applications. Complex. 2018: 7861860:1-7861860:3 (2018) - [j115]Wei Wu, Bin Li, Ling Chen, Xingquan Zhu, Chengqi Zhang:
K-Ary Tree Hashing for Fast Graph Classification. IEEE Trans. Knowl. Data Eng. 30(5): 936-949 (2018) - [j114]Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Xindong Wu:
Multi-Instance Learning with Discriminative Bag Mapping. IEEE Trans. Knowl. Data Eng. 30(6): 1065-1080 (2018) - [j113]Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Multiple Structure-View Learning for Graph Classification. IEEE Trans. Neural Networks Learn. Syst. 29(7): 3236-3251 (2018) - [j112]Zhihui Li, Feiping Nie, Xiaojun Chang, Yi Yang, Chengqi Zhang, Nicu Sebe:
Dynamic Affinity Graph Construction for Spectral Clustering Using Multiple Features. IEEE Trans. Neural Networks Learn. Syst. 29(12): 6323-6332 (2018) - [j111]Qinzhe Zhang, Jia Wu, Qin Zhang, Peng Zhang, Guodong Long, Chengqi Zhang:
Dual influence embedded social recommendation. World Wide Web 21(4): 849-874 (2018) - [c202]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, Chengqi Zhang:
DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding. AAAI 2018: 5446-5455 - [c201]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
SINE: Scalable Incomplete Network Embedding. ICDM 2018: 737-746 - [c200]Hong Yang, Shirui Pan, Peng Zhang, Ling Chen, Defu Lian, Chengqi Zhang:
Binarized attributed network embedding. ICDM 2018: 1476-1481 - [c199]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling. ICLR (Poster) 2018 - [c198]Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang:
Adversarially Regularized Graph Autoencoder for Graph Embedding. IJCAI 2018: 2609-2615 - [c197]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang:
Efficient Attributed Network Embedding via Recursive Randomized Hashing. IJCAI 2018: 2861-2867 - [c196]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, Chengqi Zhang:
Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling. IJCAI 2018: 4345-4352 - [c195]Xinxin Jiang, Shirui Pan, Guodong Long, Jiang Chang, Jing Jiang, Chengqi Zhang:
Cost-sensitive Hybrid Neural Networks for Heterogeneous and Imbalanced Data. IJCNN 2018: 1-8 - [c194]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding. PAKDD (2) 2018: 196-208 - [i14]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Network Representation Learning: A Survey. CoRR abs/1801.05852 (2018) - [i13]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, Chengqi Zhang:
Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling. CoRR abs/1801.10296 (2018) - [i12]Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang:
Adversarially Regularized Graph Autoencoder. CoRR abs/1802.04407 (2018) - [i11]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding. CoRR abs/1803.02533 (2018) - [i10]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling. CoRR abs/1804.00857 (2018) - [i9]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Fast Directional Self-Attention Mechanism. CoRR abs/1805.00912 (2018) - [i8]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
SINE: Scalable Incomplete Network Embedding. CoRR abs/1810.06768 (2018) - [i7]Wei Wu, Bin Li, Ling Chen, Junbin Gao, Chengqi Zhang:
A Review for Weighted MinHash Algorithms. CoRR abs/1811.04633 (2018) - 2017
- [j110]Qinzhe Zhang, Jia Wu, Peng Zhang, Guodong Long, Chengqi Zhang:
Collective Hyping Detection System for Identifying Online Spam Activities. IEEE Intell. Syst. 32(5): 53-63 (2017) - [j109]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Boosting for graph classification with universum. Knowl. Inf. Syst. 50(1): 53-77 (2017) - [j108]Qingfeng Chen, Yiqi Wang, Baoshan Chen, Chengqi Zhang, Lusheng Wang, Jinyan Li:
Using propensity scores to predict the kinases of unannotated phosphopeptides. Knowl. Based Syst. 135: 60-76 (2017) - [j107]Qingfeng Chen, Chaowang Lan, Baoshan Chen, Lusheng Wang, Jinyan Li, Chengqi Zhang:
Exploring Consensus RNA Substructural Patterns Using Subgraph Mining. IEEE ACM Trans. Comput. Biol. Bioinform. 14(5): 1134-1146 (2017) - [j106]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Task Sensitive Feature Exploration and Learning for Multitask Graph Classification. IEEE Trans. Cybern. 47(3): 744-758 (2017) - [j105]Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Xindong Wu:
Positive and Unlabeled Multi-Graph Learning. IEEE Trans. Cybern. 47(4): 818-829 (2017) - [j104]Ting Guo, Jia Wu, Xingquan Zhu, Chengqi Zhang:
Combining Structured Node Content and Topology Information for Networked Graph Clustering. ACM Trans. Knowl. Discov. Data 11(3): 29:1-29:29 (2017) - [j103]Haishuai Wang, Peng Zhang, Xingquan Zhu, Ivor Wai-Hung Tsang, Ling Chen, Chengqi Zhang, Xindong Wu:
Incremental Subgraph Feature Selection for Graph Classification. IEEE Trans. Knowl. Data Eng. 29(1): 128-142 (2017) - [c193]Bozhong Liu, Ling Chen, Xingquan Zhu, Ying Zhang, Chengqi Zhang, Weidong Qiu:
Protecting Location Privacy in Spatial Crowdsourcing using Encrypted Data. EDBT 2017: 478-481 - [c192]Kaisong Song, Wei Gao, Shi Feng, Daling Wang, Kam-Fai Wong, Chengqi Zhang:
Recommendation vs Sentiment Analysis: A Text-Driven Latent Factor Model for Rating Prediction with Cold-Start Awareness. IJCAI 2017: 2744-2750 - [c191]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
User Profile Preserving Social Network Embedding. IJCAI 2017: 3378-3384 - [c190]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang:
Consistent Weighted Sampling Made More Practical. WWW 2017: 1035-1043 - [i6]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang, Philip S. Yu:
Improved Consistent Weighted Sampling Revisited. CoRR abs/1706.01172 (2017) - [i5]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, Chengqi Zhang:
DiSAN: Directional Self-Attention Network for RNN/CNN-free Language Understanding. CoRR abs/1709.04696 (2017) - [i4]Jiangchao Yao, Jiajie Wang, Ivor W. Tsang, Ya Zhang, Jun Sun, Chengqi Zhang, Rui Zhang:
Deep Learning from Noisy Image Labels with Quality Embedding. CoRR abs/1711.00583 (2017) - 2016
- [j102]Qingfeng Chen, Yi-Ping Phoebe Chen, Chengqi Zhang:
Interval-Based Similarity for Classifying Conserved RNA Secondary Structures. IEEE Intell. Syst. 31(3): 78-85 (2016) - [j101]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Multi-graph-view subgraph mining for graph classification. Knowl. Inf. Syst. 48(1): 29-54 (2016) - [j100]Jia Wu, Shirui Pan, Xingquan Zhu, Peng Zhang, Chengqi Zhang:
SODE: Self-Adaptive One-Dependence Estimators for classification. Pattern Recognit. 51: 358-377 (2016) - [j99]Xiaojun Chang, Feiping Nie, Yi Yang, Chengqi Zhang, Heng Huang:
Convex Sparse PCA for Unsupervised Feature Learning. ACM Trans. Knowl. Discov. Data 11(1): 3:1-3:16 (2016) - [j98]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Joint Structure Feature Exploration and Regularization for Multi-Task Graph Classification. IEEE Trans. Knowl. Data Eng. 28(3): 715-728 (2016) - [j97]Qin Zhang, Peng Zhang, Guodong Long, Wei Ding, Chengqi Zhang, Xindong Wu:
Online Learning from Trapezoidal Data Streams. IEEE Trans. Knowl. Data Eng. 28(10): 2709-2723 (2016) - [j96]Xiaojun Chang, Feiping Nie, Sen Wang, Yi Yang, Xiaofang Zhou, Chengqi Zhang:
Compound Rank-k Projections for Bilinear Analysis. IEEE Trans. Neural Networks Learn. Syst. 27(7): 1502-1513 (2016) - [j95]Peng Zhang, Jing He, Guodong Long, Guangyan Huang, Chengqi Zhang:
Towards Anomalous Diffusion Sources Detection in a Large Network. ACM Trans. Internet Techn. 16(1): 2:1-2:24 (2016) - [c189]Xiaojun Chang, Yi Yang, Guodong Long, Chengqi Zhang, Alexander G. Hauptmann:
Dynamic Concept Composition for Zero-Example Event Detection. AAAI 2016: 3464-3470 - [c188]Bozhong Liu, Ling Chen, Chunyang Liu, Chengqi Zhang, Weidong Qiu:
Mining Co-locations from Continuously Distributed Uncertain Spatial Data. APWeb (1) 2016: 66-78 - [c187]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Collective Classification via Discriminative Matrix Factorization on Sparsely Labeled Networks. CIKM 2016: 1563-1572 - [c186]Qinzhe Zhang, Jia Wu, Hong Yang, Weixue Lu, Guodong Long, Chengqi Zhang:
Global and Local Influence-based Social Recommendation. CIKM 2016: 1917-1920 - [c185]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Joint structure feature exploration and regularization for multi-task graph classification. ICDE 2016: 1474-1475 - [c184]Meng Fang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
TrGraph: Cross-network transfer learning via common signature subgraphs. ICDE 2016: 1534-1535 - [c183]Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
Homophily, Structure, and Content Augmented Network Representation Learning. ICDM 2016: 609-618 - [c182]Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, Ivor W. Tsang, Chengqi Zhang:
Inferring Latent Network from Cascade Data for Dynamic Social Recommendation. ICDM 2016: 669-678 - [c181]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang:
Canonical Consistent Weighted Sampling for Real-Value Weighted Min-Hash. ICDM 2016: 1287-1292 - [c180]Qingfeng Chen, Chaowang Lan, Jinyan Li, Baoshan Chen, Lusheng Wang, Chengqi Zhang:
Depth-First Search Encoding of RNA Substructures. ICIC (1) 2016: 328-334 - [c179]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Yang Wang:
Tri-Party Deep Network Representation. IJCAI 2016: 1895-1901 - [c178]Qin Zhang, Jia Wu, Hong Yang, Yingjie Tian, Chengqi Zhang:
Unsupervised Feature Learning from Time Series. IJCAI 2016: 2322-2328 - [c177]Ruiqi Hu, Shirui Pan, Guodong Long, Xingquan Zhu, Jing Jiang, Chengqi Zhang:
Co-clustering enterprise social networks. IJCNN 2016: 107-114 - [c176]Qinzhe Zhang, Qin Zhang, Guodong Long, Peng Zhang, Chengqi Zhang:
Exploring Heterogeneous Product Networks for Discovering Collective Marketing Hyping Behavior. PAKDD (1) 2016: 40-51 - [c175]Wei Wu, Bin Li, Ling Chen, Chengqi Zhang:
Cross-View Feature Hashing for Image Retrieval. PAKDD (1) 2016: 203-214 - [c174]Kaisong Song, Wei Gao, Ling Chen, Shi Feng, Daling Wang, Chengqi Zhang:
Build Emotion Lexicon from the Mood of Crowd via Topic-Assisted Joint Non-negative Matrix Factorization. SIGIR 2016: 773-776 - [c173]Kaisong Song, Ling Chen, Wei Gao, Shi Feng, Daling Wang, Chengqi Zhang:
PerSentiment: A Personalized Sentiment Classification System for Microblog Users. WWW (Companion Volume) 2016: 255-258 - [i3]Xiaojun Chang, Yi Yang, Guodong Long, Chengqi Zhang, Alexander G. Hauptmann:
Dynamic Concept Composition for Zero-Example Event Detection. CoRR abs/1601.03679 (2016) - [i2]Haishuai Wang, Jia Wu, Xingquan Zhu, Chengqi Zhang:
Time-Variant Graph Classification. CoRR abs/1609.04350 (2016) - 2015
- [j94]Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai, Peng Zhang, Chengqi Zhang:
Self-adaptive attribute weighting for Naive Bayes classification. Expert Syst. Appl. 42(3): 1487-1502 (2015) - [j93]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Finding the best not the most: regularized loss minimization subgraph selection for graph classification. Pattern Recognit. 48(11): 3783-3796 (2015) - [j92]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang:
Graph Ensemble Boosting for Imbalanced Noisy Graph Stream Classification. IEEE Trans. Cybern. 45(5): 940-954 (2015) - [j91]Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang:
Rating Knowledge Sharing in Cross-Domain Collaborative Filtering. IEEE Trans. Cybern. 45(5): 1054-1068 (2015) - [j90]Hongzhi Yin, Bin Cui, Ling Chen, Zhiting Hu, Chengqi Zhang:
Modeling Location-Based User Rating Profiles for Personalized Recommendation. ACM Trans. Knowl. Discov. Data 9(3): 19:1-19:41 (2015) - [j89]Meng Fang, Jie Yin, Xingquan Zhu, Chengqi Zhang:
TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs. IEEE Trans. Knowl. Data Eng. 27(9): 2536-2549 (2015) - [c172]Haishuai Wang, Peng Zhang, Ling Chen, Chengqi Zhang:
SocialAnalysis: A Real-Time Query and Mining System from Social Media Data Streams. ADC 2015: 318-322 - [c171]Haishuai Wang, Peng Zhang, Ivor W. Tsang, Ling Chen, Chengqi Zhang:
Defragging Subgraph Features for Graph Classification. CIKM 2015: 1687-1690 - [c170]Kaisong Song, Shi Feng, Wei Gao, Daling Wang, Ling Chen, Chengqi Zhang:
Build Emotion Lexicon from Microblogs by Combining Effects of Seed Words and Emoticons in a Heterogeneous Graph. HT 2015: 283-292 - [c169]Qin Zhang, Peng Zhang, Guodong Long, Wei Ding, Chengqi Zhang, Xindong Wu:
Towards Mining Trapezoidal Data Streams. ICDM 2015: 1111-1116 - [c168]Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Multi-Graph-View Learning for Complicated Object Classification. IJCAI 2015: 3953-3959 - [c167]Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Chengqi Zhang, Qinfeng Shi:
Scalable Maximum Margin Matrix Factorization by Active Riemannian Subspace Search. IJCAI 2015: 3988-3994 - [c166]Haishuai Wang, Peng Zhang, Ling Chen, Huan Liu, Chengqi Zhang:
Online diffusion source detection in social networks. IJCNN 2015: 1-8 - [c165]Lu Qin, Rong-Hua Li, Lijun Chang, Chengqi Zhang:
Locally Densest Subgraph Discovery. KDD 2015: 965-974 - [c164]Bozhong Liu, Ling Chen, Chunyang Liu, Chengqi Zhang, Weidong Qiu:
RCP Mining: Towards the Summarization of Spatial Co-location Patterns. SSTD 2015: 451-469 - [e14]Chengqi Zhang, Wei Huang, Yong Shi, Philip S. Yu, Yangyong Zhu, Yingjie Tian, Peng Zhang, Jing He:
Data Science - Second International Conference, ICDS 2015 Sydney, Australia, August 8-9, 2015. Proceedings. Lecture Notes in Computer Science 9208, Springer 2015, ISBN 978-3-319-24473-0 [contents] - [e13]Longbing Cao, Chengqi Zhang, Thorsten Joachims, Geoffrey I. Webb, Dragos D. Margineantu, Graham Williams:
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, NSW, Australia, August 10-13, 2015. ACM 2015, ISBN 978-1-4503-3664-2 [contents] - 2014
- [j88]Guohua Liang, Xingquan Zhu, Chengqi Zhang:
The effect of varying levels of class distribution on bagging for different algorithms: An empirical study. Int. J. Mach. Learn. Cybern. 5(1): 63-71 (2014) - [j87]Yifan Fu, Bin Li, Xingquan Zhu, Chengqi Zhang:
Active Learning without Knowing Individual Instance Labels: A Pairwise Label Homogeneity Query Approach. IEEE Trans. Knowl. Data Eng. 26(4): 808-822 (2014) - [j86]Jia Wu, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Bag Constrained Structure Pattern Mining for Multi-Graph Classification. IEEE Trans. Knowl. Data Eng. 26(10): 2382-2396 (2014) - [c163]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning. CIKM 2014: 1699-1708 - [c162]Ting Guo, Xingquan Zhu, Jian Pei, Chengqi Zhang:
SNOC: Streaming Network Node Classification. ICDM 2014: 150-159 - [c161]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Multi-graph-view Learning for Graph Classification. ICDM 2014: 590-599 - [c160]Jia Wu, Shirui Pan, Zhihua Cai, Xingquan Zhu, Chengqi Zhang:
Dual instance and attribute weighting for Naive Bayes classification. IJCNN 2014: 1675-1679 - [c159]Jia Wu, Zhihua Cai, Shirui Pan, Xingquan Zhu, Chengqi Zhang:
Attribute weighting: How and when does it work for Bayesian Network Classification. IJCNN 2014: 4076-4083 - [c158]Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-Instance Learning from Positive and Unlabeled Bags. PAKDD (1) 2014: 237-248 - [c157]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-Graph Learning with Positive and Unlabeled Bags. SDM 2014: 217-225 - [c156]Lu Qin, Jeffrey Xu Yu, Lijun Chang, Hong Cheng, Chengqi Zhang, Xuemin Lin:
Scalable big graph processing in MapReduce. SIGMOD Conference 2014: 827-838 - [c155]Ying Zhang, Wenjie Zhang, Xuemin Lin, Muhammad Aamir Cheema, Chengqi Zhang:
Matching dominance: capture the semantics of dominance for multi-dimensional uncertain objects. SSDBM 2014: 18:1-18:12 - 2013
- [j85]Jun Li, Wei Bian, Dacheng Tao, Chengqi Zhang:
Learning colours from textures by sparse manifold embedding. Signal Process. 93(6): 1485-1495 (2013) - [j84]Bin Li, Ling Chen, Xingquan Zhu, Chengqi Zhang:
Noisy but non-malicious user detection in social recommender systems. World Wide Web 16(5-6): 677-699 (2013) - [c154]Li Wan, Ling Chen, Chengqi Zhang:
Mining frequent serial episodes over uncertain sequence data. EDBT 2013: 215-226 - [c153]Shirui Pan, Xingquan Zhu, Chengqi Zhang, Philip S. Yu:
Graph stream classification using labeled and unlabeled graphs. ICDE 2013: 398-409 - [c152]Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-instance Multi-graph Dual Embedding Learning. ICDM 2013: 827-836 - [c151]Li Wan, Ling Chen, Chengqi Zhang:
Mining Dependent Frequent Serial Episodes from Uncertain Sequence Data. ICDM 2013: 1211-1216 - [c150]Chunyang Liu, Ling Chen, Chengqi Zhang:
Summarizing probabilistic frequent patterns: a fast approach. KDD 2013: 527-535 - [c149]Zhenxing Qin, Alan Tao Wang, Chengqi Zhang, Shichao Zhang:
Cost-Sensitive Classification with k-Nearest Neighbors. KSEM 2013: 112-131 - [c148]Ling Chen, Chunyang Liu, Chengqi Zhang:
Mining Probabilistic Representative Frequent Patterns From Uncertain Data. SDM 2013: 73-81 - [c147]Meng Fang, Jie Yin, Chengqi Zhang, Xingquan Zhu:
Active Class Discovery and Learning for Networked Data. SDM 2013: 315-323 - 2012
- [j83]Shichao Zhang, Feng Chen, Xindong Wu, Chengqi Zhang, Ruili Wang:
Mining bridging rules between conceptual clusters. Appl. Intell. 36(1): 108-118 (2012) - [j82]Tao Wang, Zhenxing Qin, Shichao Zhang, Chengqi Zhang:
Cost-sensitive classification with inadequate labeled data. Inf. Syst. 37(5): 508-516 (2012) - [j81]Mingli Song, Dacheng Tao, Chun Chen, Jiajun Bu, Jiebo Luo, Chengqi Zhang:
Probabilistic Exposure Fusion. IEEE Trans. Image Process. 21(1): 341-357 (2012) - [c146]Meng Fang, Xingquan Zhu, Chengqi Zhang:
Active Learning from Oracle with Knowledge Blind Spot. AAAI 2012: 2421-2422 - [c145]Xinhua Zhu, Yaxin Yu, Yuming Ou, Dan Luo, Chengqi Zhang, Jiahang Chen:
System Modeling of a Smart-Home Healthy Lifestyle Assistant. ADMI 2012: 65-78 - [c144]Guohua Liang, Chengqi Zhang:
A Comparative Study of Sampling Methods and Algorithms for Imbalanced Time Series Classification. Australasian Conference on Artificial Intelligence 2012: 637-648 - [c143]Guodong Long, Ling Chen, Xingquan Zhu, Chengqi Zhang:
TCSST: transfer classification of short & sparse text using external data. CIKM 2012: 764-772 - [c142]Guohua Liang, Chengqi Zhang:
An efficient and simple under-sampling technique for imbalanced time series classification. CIKM 2012: 2339-2342 - [c141]Bin Li, Xingquan Zhu, Lianhua Chi, Chengqi Zhang:
Nested Subtree Hash Kernels for Large-Scale Graph Classification over Streams. ICDM 2012: 399-408 - [c140]Guoxin Su, Mingsheng Ying, Chengqi Zhang:
Semantic Analysis of Component-aspect Dynamism for Connector-based Architecture Styles. WICSA/ECSA 2012: 151-160 - [i1]Guoxin Su, Mingsheng Ying, Chengqi Zhang:
Session Communication and Integration. CoRR abs/1210.2125 (2012) - 2011
- [j80]Xingquan Zhu, Bin Li, Xindong Wu, Dan He, Chengqi Zhang:
CLAP: Collaborative pattern mining for distributed information systems. Decis. Support Syst. 52(1): 40-51 (2011) - [j79]Tao Yang, Vojislav Kecman, Longbing Cao, Chengqi Zhang, Joshua Zhexue Huang:
Margin-based ensemble classifier for protein fold recognition. Expert Syst. Appl. 38(10): 12348-12355 (2011) - [j78]Yanchang Zhao, Jie Cao, Chengqi Zhang, Shichao Zhang:
Enhancing grid-density based clustering for high dimensional data. J. Syst. Softw. 84(9): 1524-1539 (2011) - [j77]Xingquan Zhu, Wei Ding, Philip S. Yu, Chengqi Zhang:
One-class learning and concept summarization for data streams. Knowl. Inf. Syst. 28(3): 523-553 (2011) - [j76]Longbing Cao, Huaifeng Zhang, Yanchang Zhao, Dan Luo, Chengqi Zhang:
Combined Mining: Discovering Informative Knowledge in Complex Data. IEEE Trans. Syst. Man Cybern. Part B 41(3): 699-712 (2011) - [c139]Guohua Liang, Xingquan Zhu, Chengqi Zhang:
An Empirical Study of Bagging Predictors for Different Learning Algorithms. AAAI 2011: 1802-1803 - [c138]Guohua Liang, Chengqi Zhang:
An Empirical Evaluation of Bagging with Different Algorithms on Imbalanced Data. ADMA (1) 2011: 339-352 - [c137]Guohua Liang, Xingquan Zhu, Chengqi Zhang:
An Empirical Study of Bagging Predictors for Imbalanced Data with Different Levels of Class Distribution. Australasian Conference on Artificial Intelligence 2011: 213-222 - [c136]Jun Li, Wei Bian, Dacheng Tao, Chengqi Zhang:
Learning Colours from Textures by Sparse Manifold Embedding. Australasian Conference on Artificial Intelligence 2011: 600-608 - [c135]Guohua Liang, Chengqi Zhang:
Empirical Study of Bagging Predictors on Medical Data. AusDM 2011: 31-40 - [c134]Xiangjun Dong, Zhigang Zheng, Longbing Cao, Yanchang Zhao, Chengqi Zhang, Jinjiu Li, Wei Wei, Yuming Ou:
e-NSP: efficient negative sequential pattern mining based on identified positive patterns without database rescanning. CIKM 2011: 825-830 - [c133]Yifan Fu, Bin Li, Xingquan Zhu, Chengqi Zhang:
Do they belong to the same class: active learning by querying pairwise label homogeneity. CIKM 2011: 2161-2164 - [c132]Yanshan Xiao, Bo Liu, Jie Yin, Longbing Cao, Chengqi Zhang, Zhifeng Hao:
Similarity-Based Approach for Positive and Unlabeled Learning. IJCAI 2011: 1577-1582 - [c131]Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Xiangyang Xue, Xindong Wu:
Cross-Domain Collaborative Filtering over Time. IJCAI 2011: 2293-2298 - [c130]Chao Luo, Yanchang Zhao, Dan Luo, Chengqi Zhang, Wei Cao:
Agent-Based Subspace Clustering. PAKDD (2) 2011: 370-381 - [c129]Ling Chen, Chengqi Zhang:
Semi-supervised Variable Weighting for Clustering. SDM 2011: 862-871 - 2010
- [j75]Dingrong Yuan, Xiaofang You, Chengqi Zhang:
Against-Expectation Pattern Discovery: Identifying Interactions within Items with Large Relative-Contrasts in Databases. IEEE Intell. Informatics Bull. 11(1): 14-23 (2010) - [j74]Yongsong Qin, Shichao Zhang, Chengqi Zhang:
Combining kNN Imputation and Bootstrap Calibrated: Empirical Likelihood for Incomplete Data Analysis. Int. J. Data Warehous. Min. 6(4): 61-73 (2010) - [j73]Chengqi Zhang, Philip S. Yu, David A. Bell:
Introduction to the Domain-Driven Data Mining Special Section. IEEE Trans. Knowl. Data Eng. 22(6): 753-754 (2010) - [j72]Longbing Cao, Yanchang Zhao, Huaifeng Zhang, Dan Luo, Chengqi Zhang, Eun K. Park:
Flexible Frameworks for Actionable Knowledge Discovery. IEEE Trans. Knowl. Data Eng. 22(9): 1299-1312 (2010) - [c128]Zhenxing Qin, Chengqi Zhang, Tao Wang, Shichao Zhang:
Cost Sensitive Classification in Data Mining. ADMA (1) 2010: 1-11 - [c127]Yong Yang, Dan Luo, Chengqi Zhang:
A Multiple System Performance Monitoring Model for Web Services. ADMI 2010: 149-161 - [c126]Guoxin Su, Mingsheng Ying, Chengqi Zhang:
An ADL-Approach to Specifying and Analyzing Centralized-Mode Architectural Connection. ECSA 2010: 8-23 - [c125]Tao Yang, Vojislav Kecman, Longbing Cao, Chengqi Zhang:
Testing Adaptive Local Hyperplane for multi-class classification by double cross-validation. IJCNN 2010: 1-5 - [c124]Tao Yang, Vojislav Kecman, Longbing Cao, Chengqi Zhang:
Combining Support Vector Machines and the t-statistic for Gene Selection in DNA Microarray Data Analysis. PAKDD (2) 2010: 55-62 - [c123]Tao Yang, Longbing Cao, Chengqi Zhang:
A Novel Prototype Reduction Method for the K-Nearest Neighbor Algorithm with K >= 1. PAKDD (2) 2010: 89-100 - [e12]Geoffrey I. Webb, Bing Liu, Chengqi Zhang, Dimitrios Gunopulos, Xindong Wu:
ICDM 2010, The 10th IEEE International Conference on Data Mining, Sydney, Australia, 14-17 December 2010. IEEE Computer Society 2010, ISBN 978-0-7695-4256-0 [contents] - [e11]Wei Fan, Wynne Hsu, Geoffrey I. Webb, Bing Liu, Chengqi Zhang, Dimitrios Gunopulos, Xindong Wu:
ICDMW 2010, The 10th IEEE International Conference on Data Mining Workshops, Sydney, Australia, 13 December 2010. IEEE Computer Society 2010, ISBN 978-0-7695-4257-7 [contents]
2000 – 2009
- 2009
- [j71]Xiaowei Yan, Chengqi Zhang, Shichao Zhang:
Confidence Metrics for Association Rule Mining. Appl. Artif. Intell. 23(8): 713-737 (2009) - [j70]Yuming Ou, Longbing Cao, Chengqi Zhang:
Adaptive Anomaly Detection of Coupled Activity Sequences. IEEE Intell. Informatics Bull. 10(1): 12-16 (2009) - [j69]Yongsong Qin, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
POP algorithm: Kernel-based imputation to treat missing values in knowledge discovery from databases. Expert Syst. Appl. 36(2): 2794-2804 (2009) - [j68]Xiaowei Yan, Chengqi Zhang, Shichao Zhang:
Genetic algorithm-based strategy for identifying association rules without specifying actual minimum support. Expert Syst. Appl. 36(2): 3066-3076 (2009) - [j67]Yongsong Qin, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Estimating confidence intervals for structural differences between contrast groups with missing data. Expert Syst. Appl. 36(3): 6431-6438 (2009) - [j66]Zili Zhang, Pengyi Yang, Xindong Wu, Chengqi Zhang:
An Agent-Based Hybrid System for Microarray Data Analysis. IEEE Intell. Syst. 24(5): 53-63 (2009) - [j65]Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Customer Activity Sequence Classification for Debt Prevention in Social Security. J. Comput. Sci. Technol. 24(6): 1000-1009 (2009) - [c122]Longbing Cao, Dan Luo, Chengqi Zhang:
Ubiquitous Intelligence in Agent Mining. ADMI 2009: 23-35 - [c121]Yanshan Xiao, Bo Liu, Longbing Cao, Xindong Wu, Chengqi Zhang, Zhifeng Hao, Fengzhao Yang, Jie Cao:
Multi-sphere Support Vector Data Description for Outliers Detection on Multi-distribution Data. ICDM Workshops 2009: 82-87 - [c120]Xingquan Zhu, Xindong Wu, Chengqi Zhang:
Vague One-Class Learning for Data Streams. ICDM 2009: 657-666 - [c119]Shanshan Wu, Yanchang Zhao, Huaifeng Zhang, Chengqi Zhang, Longbing Cao, Hans Bohlscheid:
Debt Detection in Social Security by Adaptive Sequence Classification. KSEM 2009: 192-203 - [c118]Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Mining Both Positive and Negative Impact-Oriented Sequential Rules from Transactional Data. PAKDD 2009: 656-663 - [c117]Yanchang Zhao, Huaifeng Zhang, Shanshan Wu, Jian Pei, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns. ECML/PKDD (2) 2009: 648-663 - [c116]Wei Wang, Chuan Xiao, Xuemin Lin, Chengqi Zhang:
Efficient approximate entity extraction with edit distance constraints. SIGMOD Conference 2009: 759-770 - [c115]Chengqi Zhang:
Developing Actionable Trading Strategies for Trading Agents. Web Intelligence 2009: 9 - [p4]Chayapol Moemeng, Vladimir Gorodetsky, Ziye Zuo, Yong Yang, Chengqi Zhang:
Agent-Based Distributed Data Mining: A Survey. Data Mining and Multi-agent Integration 2009: 47-58 - 2008
- [b5]Qingfeng Chen, Chengqi Zhang, Shichao Zhang:
Secure Transaction Protocol Analysis: Models and Applications. Lecture Notes in Computer Science 5111, Springer 2008, ISBN 978-3-540-85073-1 - [j64]Longbing Cao, Yanchang Zhao, Chengqi Zhang, Huaifeng Zhang:
Activity Mining: from Activities to Actions. Int. J. Inf. Technol. Decis. Mak. 7(2): 259-273 (2008) - [j63]Xingquan Zhu, Chengqi Zhang, David L. Olson:
Editorial. Int. J. Softw. Informatics 2(2): 89-93 (2008) - [j62]Shichao Zhang, Xindong Wu, Chengqi Zhang, Jingli Lu:
Computing the minimum-support for mining frequent patterns. Knowl. Inf. Syst. 15(2): 233-257 (2008) - [j61]Shichao Zhang, Jilian Zhang, Xiaofeng Zhu, Yongsong Qin, Chengqi Zhang:
Missing Value Imputation Based on Data Clustering. Trans. Comput. Sci. 1: 128-138 (2008) - [j60]Longbing Cao, Yanchang Zhao, Chengqi Zhang:
Mining Impact-Targeted Activity Patterns in Imbalanced Data. IEEE Trans. Knowl. Data Eng. 20(8): 1053-1066 (2008) - [j59]Longbing Cao, Chengqi Zhang, MengChu Zhou:
Engineering Open Complex Agent Systems: A Case Study. IEEE Trans. Syst. Man Cybern. Part C 38(4): 483-496 (2008) - [c114]Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Combined Pattern Mining: From Learned Rules to Actionable Knowledge. Australasian Conference on Artificial Intelligence 2008: 393-403 - [c113]Peerapol Moemeng, Longbing Cao, Chengqi Zhang:
F-TRADE 3.0: An Agent-Based Integrated Framework for Data Mining Experiments. Web Intelligence/IAT Workshops 2008: 612-615 - [c112]Chao Luo, Yanchang Zhao, Longbing Cao, Yuming Ou, Chengqi Zhang:
Exception Mining on Multiple Time Series in Stock Market. Web Intelligence/IAT Workshops 2008: 690-693 - [c111]Bo Liu, Longbing Cao, Philip S. Yu, Chengqi Zhang:
Multi-Space-Mapped SVMs for Multi-class Classification. ICDM 2008: 911-916 - [c110]Xingquan Zhu, Peng Zhang, Xindong Wu, Dan He, Chengqi Zhang, Yong Shi:
Cleansing Noisy Data Streams. ICDM 2008: 1139-1144 - [c109]Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang:
Combined Association Rule Mining. PAKDD 2008: 1069-1074 - [c108]Yuming Ou, Longbing Cao, Chao Luo, Chengqi Zhang:
Domain-Driven Local Exceptional Pattern Mining for Detecting Stock Price Manipulation. PRICAI 2008: 849-858 - [c107]Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Efficient Mining of Event-Oriented Negative Sequential Rules. Web Intelligence 2008: 336-342 - [p3]Chengqi Zhang, Zili Zhang:
Intelligent Agent. Wiley Encyclopedia of Computer Science and Engineering 2008 - 2007
- [j58]Xiaowei Yan, Shichao Zhang, Chengqi Zhang:
On Data Structures for Association Rule Discovery. Appl. Artif. Intell. 21(2): 57-79 (2007) - [j57]Yongsong Qin, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Semi-parametric optimization for missing data imputation. Appl. Intell. 27(1): 79-88 (2007) - [j56]Qingfeng Chen, Yi-Ping Phoebe Chen, Chengqi Zhang:
Detecting inconsistency in biological molecular databases using ontologies. Data Min. Knowl. Discov. 15(2): 275-296 (2007) - [j55]Longbing Cao, Chengqi Zhang, Qiang Yang, David A. Bell, Michail Vlachos, Bahar Taneri, Eamonn J. Keogh, Philip S. Yu, Ning Zhong, Mafruz Zaman Ashrafi, David Taniar, Eugene Dubossarsky, Warwick Graco:
Domain-Driven, Actionable Knowledge Discovery. IEEE Intell. Syst. 22(4): 78-88 (2007) - [j54]Longbing Cao, Dan Luo, Chengqi Zhang:
Knowledge actionability: satisfying technical and business interestingness. Int. J. Bus. Intell. Data Min. 2(4): 496-514 (2007) - [j53]Longbing Cao, Chengqi Zhang:
The Evolution of KDD: towards Domain-Driven Data Mining. Int. J. Pattern Recognit. Artif. Intell. 21(4): 677-692 (2007) - [j52]Shichao Zhang, Jilian Zhang, Chengqi Zhang:
EDUA: An efficient algorithm for dynamic database mining. Inf. Sci. 177(13): 2756-2767 (2007) - [j51]Longbing Cao, Chengqi Zhang, Yanchang Zhao, Philip S. Yu, Graham Williams:
DDDM2007: Domain Driven Data Mining. SIGKDD Explor. 9(2): 84-86 (2007) - [j50]Zili Zhang, Chengqi Zhang:
Building agent-based hybrid intelligent systems: A case study. Web Intell. Agent Syst. 5(3): 255-271 (2007) - [c106]Jilian Zhang, Shichao Zhang, Xiaofeng Zhu, Xindong Wu, Chengqi Zhang:
Measuring the Uncertainty of Differences for Contrasting Groups. AAAI 2007: 1920-1921 - [c105]Xiaofeng Zhu, Shichao Zhang, Jilian Zhang, Chengqi Zhang:
Cost-Sensitive Imputing Missing Values with Ordering. AAAI 2007: 1922-1923 - [c104]Longbing Cao, Chao Luo, Chengqi Zhang:
Agent-Mining Interaction: An Emerging Area. AIS-ADM 2007: 60-73 - [c103]Longbing Cao, Chengqi Zhang:
F-trade: an agent-mining symbiont for financial services. AAMAS 2007: 262 - [c102]Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang:
Class Association Rule Mining with Multiple Imbalanced Attributes. Australian Conference on Artificial Intelligence 2007: 827-831 - [c101]Longbing Cao, Chao Luo, Chengqi Zhang:
Developing Actionable Trading Strategies for Trading Agents. IAT 2007: 72-75 - [c100]Yuming Ou, Longbing Cao, Ting Yu, Chengqi Zhang:
Detecting Turning Points of Trading Price and Return Volatility for Market Surveillance Agents. Web Intelligence/IAT Workshops 2007: 491-494 - [c99]Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Cost-Time Sensitive Decision Tree with Missing Values. KSEM 2007: 447-459 - [c98]Jiarui Ni, Longbing Cao, Chengqi Zhang:
Evolutionary Optimization of Trading Strategies. DMBiz@PAKDD 2007: 11-24 - [c97]Dan Luo, Longbing Cao, Chao Luo, Chengqi Zhang, Weiyuan Wang:
Towards Business Interestingness in Actionable Knowledge Discovery. DMBiz@PAKDD 2007: 99-109 - [c96]Chengqi Zhang, Xiaofeng Zhu, Jilian Zhang, Yongsong Qin, Shichao Zhang:
GBKII: An Imputation Method for Missing Values. PAKDD 2007: 1080-1087 - [c95]Zhangyan Xu, Chengqi Zhang, Shichao Zhang, Wei Song, Bingru Yang:
Efficient Attribute Reduction Based on Discernibility Matrix. RSKT 2007: 13-21 - [e10]Vladimir Gorodetsky, Chengqi Zhang, Victor A. Skormin, Longbing Cao:
Autonomous Intelligent Systems: Multi-Agents and Data Mining, Second International Workshop, AIS-ADM 2007, St. Petersburg, Russia, June 3-5, 2007, Proceedings. Lecture Notes in Computer Science 4476, Springer 2007, ISBN 978-3-540-72838-2 [contents] - 2006
- [j49]Yue Xu, Kankana Chakrabarty, Chengqi Zhang:
A Neural Network Abductive Model. Aust. J. Intell. Inf. Process. Syst. 9(1): 71-83 (2006) - [j48]Longbing Cao, Chengqi Zhang:
Domain-Driven Data Mining: A Practical Methodology. Int. J. Data Warehous. Min. 2(4): 49-65 (2006) - [j47]Longbing Cao, Chengqi Zhang, Jiming Liu:
Ontology-based integration of business intelligence. Web Intell. Agent Syst. 4(3): 313-325 (2006) - [c94]Chengqi Zhang, Longbing Cao:
Domain-Driven Data Mining: Methodologies and Applications. AMT 2006: 13-16 - [c93]Shichao Zhang, Yongsong Qin, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Kernel-Based Multi-Imputation for Missing Data. AMT 2006: 106-111 - [c92]Yanchang Zhao, Chengqi Zhang, Shichao Zhang:
Efficient Frequent Itemsets Mining by Sampling. AMT 2006: 112-117 - [c91]Zhenxing Qin, Shichao Zhang, Chengqi Zhang:
Missing or absent? A Question in Cost-sensitive Decision Tree. AMT 2006: 118-125 - [c90]Jiarui Ni, Longbing Cao, Chengqi Zhang:
Agent Services-Oriented Architectural Design of a Framework for Artificial Stock Markets. AMT 2006: 396-399 - [c89]Yanchang Zhao, Chengqi Zhang, Shichao Zhang, Lianwei Zhao:
Adapting K-Means Algorithm for Discovering Clusters in Subspaces. APWeb 2006: 53-62 - [c88]Qingfeng Chen, Yi-Ping Phoebe Chen, Shichao Zhang, Chengqi Zhang:
Detecting Collusion Attacks in Security Protocols. APWeb 2006: 297-306 - [c87]Yanchang Zhao, Chengqi Zhang, Shichao Zhang:
Enhancing DWT for Recent-Biased Dimension Reduction of Time Series Data. Australian Conference on Artificial Intelligence 2006: 1048-1053 - [c86]Yanchang Zhao, Longbing Cao, Yvonne Morrow, Yuming Ou, Jiarui Ni, Chengqi Zhang:
Discovering Debtor Patterns of Centrelink Customers. AusDM 2006: 135-144 - [c85]Jiarui Ni, Chengqi Zhang:
A dynamic storage method for stock transaction data. Computational Intelligence 2006: 350-355 - [c84]Jiarui Ni, Chengqi Zhang:
A Human-Friendly MAS for Mining Stock Data. IAT Workshops 2006: 19-22 - [c83]Longbing Cao, Chao Luo, Jiarui Ni, Dan Luo, Chengqi Zhang:
Stock Data Mining through Fuzzy Genetic Algorithms. JCIS 2006 - [c82]Shichao Zhang, Feng Chen, Xindong Wu, Chengqi Zhang:
Identifying bridging rules between conceptual clusters. KDD 2006: 815-820 - [c81]Shichao Zhang, Jeffrey Xu Yu, Jingli Lu, Chengqi Zhang:
Is Frequency Enough for Decision Makers to Make Decisions?. PAKDD 2006: 499-503 - [c80]Longbing Cao, Chengqi Zhang:
Domain-Driven Actionable Knowledge Discovery in the Real World. PAKDD 2006: 821-830 - [c79]Qingfeng Chen, Yi-Ping Phoebe Chen, Chengqi Zhang, Lianggang Li:
Mining Frequent Itemsets for Protein Kinase Regulation. PRICAI 2006: 222-230 - [c78]Longbing Cao, Dan Luo, Chengqi Zhang:
Fuzzy Genetic Algorithms for Pairs Mining. PRICAI 2006: 711-720 - [c77]Shichao Zhang, Yongsong Qin, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Optimized Parameters for Missing Data Imputation. PRICAI 2006: 1010-1016 - [c76]Jiaqi Wang, Chengqi Zhang:
Dynamic Focus Strategies for Electronic Trade Execution in Limit Order Markets. CEC/EEE 2006: 26 - [c75]