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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
[j148]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)- [j147]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) - [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 - [i57]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) - [i56]Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang, Chengqi Zhang:
Transductive Reward Inference on Graph. CoRR abs/2402.03661 (2024) - [i55]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) - [i54]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning. CoRR abs/2404.10942 (2024) - [i53]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) - [i52]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) - [i51]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) - [i50]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) - [i49]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) - [i48]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) - [i47]Zhiwei Li, Guodong Long, Tianyi Zhou, Jing Jiang, Chengqi Zhang:
Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach. CoRR abs/2408.08931 (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,