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ORCIDJia Wu 0001
Person information
- affiliation: Macquarie University, Sydney, Australia
- affiliation: China University of Geosciences, Wuhan, China
- affiliation (PhD): University of Technology Sydney, Ultimo, Australia
Other persons with the same name
- Jia Wu — disambiguation page
- Jia Wu 0002
![[0000-0001-9013-0818]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-9013-0818")
— Central South University, School of Software, Changsha, China - Jia Wu 0003 — University of Washington, Department of Electrical Engineering and Computer Science and Engineering, Seattle, WA, USA
- Jia Wu 0004 — University of Salford, School of Computing Science and Engineering, UK (and 1 more)
- Jia Wu 0005 — University of Electronic Science and Technology of China, School of Information and Software Engineering, Chengdu, China (and 1 more)
- Jia Wu 0006 — Central South University, School of Information Science and Engineering, Changsha, China
- Jia Wu 0007 — Dalian University of Technology, School of Mathematical Sciences, China
- Jia Wu 0008 — University of Pennsylvania, Department of Radiology, Philadelphia, PA, USA
- Jia Wu 0009 — University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Department of Thoracic/Head and Neck Medical Oncology, Houston, TX, USA (and 1 more)
- Jia Wu 0010 — Nanjing University of Finance and Economics, School of Information Engineering, China
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Books and Theses
- 2015
[b1]Jia Wu:
Multi-graph learning. University of Technology Sydney, Australia, 2015
Journal Articles
- 2024
- [j138]Danfeng Sun, Junjie Hu, Huifeng Wu, Jia Wu, Jian Yang, Quan Z. Sheng, Schahram Dustdar:
A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT. ACM Comput. Surv. 56(2): 50:1-50:37 (2024) - [j137]Lingfeng Zhong, Jia Wu, Qian Li, Hao Peng, Xindong Wu:
A Comprehensive Survey on Automatic Knowledge Graph Construction. ACM Comput. Surv. 56(4): 94:1-94:62 (2024) - [j136]Jiarun Fu, Rong Gao, Yonghong Yu, Jia Wu, Jing Li, Donghua Liu, Zhiwei Ye:
Contrastive graph learning long and short-term interests for POI recommendation. Expert Syst. Appl. 238(Part B): 121931 (2024) - [j135]Hao Peng, Jia Wu, Jiaxu Cui, Philip S. Yu:
Introduction to the special issue on recent advances in graph learning: theory, algorithms, applications, and systems. Int. J. Mach. Learn. Cybern. 15(1): 1-2 (2024) - [j134]Tong Liu, Jing Li, Jia Wu, Bo Du, Jun Wan, Jun Chang:
Confusable facial expression recognition with geometry-aware conditional network. Pattern Recognit. 148: 110174 (2024) - [j133]Tianpeng Liu, Jing Li, Jia Wu, Lefei Zhang, Jun Chang, Jun Wan, Lezhi Lian:
Tracking With Saliency Region Transformer. IEEE Trans. Image Process. 33: 285-296 (2024) - [j132]Xixun Lin, Chuan Zhou, Jia Wu, Lixin Zou, Shirui Pan, Yanan Cao, Bin Wang, Shuaiqiang Wang, Dawei Yin:
Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation. IEEE Trans. Knowl. Data Eng. 36(4): 1815-1828 (2024) - [j131]Jiaqian Ren, Hao Peng, Lei Jiang, Zhiwei Liu, Jia Wu, Zhengtao Yu, Philip S. Yu:
Uncertainty-Guided Boundary Learning for Imbalanced Social Event Detection. IEEE Trans. Knowl. Data Eng. 36(6): 2701-2715 (2024) - [j130]Zhenchang Xia, Nan Dong, Jia Wu, Chuanguo Ma:
Multivariate Knowledge Tracking Based on Graph Neural Network in ASSISTments. IEEE Trans. Learn. Technol. 17: 32-43 (2024) - [j129]Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu:
A Comprehensive Survey on Community Detection With Deep Learning. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4682-4702 (2024) - 2023
- [j128]Zehao Wang, Huifeng Wu, Jin Fan, Danfeng Sun, Jia Wu:
A robust feature reinforcement framework for heterogeneous graphs neural networks. Future Gener. Comput. Syst. 141: 143-153 (2023) - [j127]Naime Ranjbar Kermany, Weiliang Zhao, Tseesuren Batsuuri, Jian Yang, Jia Wu:
Incorporating user rating credibility in recommender systems. Future Gener. Comput. Syst. 147: 30-43 (2023) - [j126]Tianpeng Liu, Jing Li, Jia Wu, Jun Chang, Yafu Xiao, Yan Hong:
Visual tracking with dumbbell selection network. Neurocomputing 516: 77-91 (2023) - [j125]Bentian Li, Jia Wu, Dechang Pi, Yunxia Lin:
Dual Mutual Robust Graph Convolutional Network for Weakly Supervised Node Classification in Social Networks of Internet of People. IEEE Internet Things J. 10(16): 14798-14809 (2023) - [j124]Xingcheng Fu, Jianxin Li, Jia Wu, Jiawen Qin, Qingyun Sun, Cheng Ji, Senzhang Wang, Hao Peng, Philip S. Yu:
Adaptive curvature exploration geometric graph neural network. Knowl. Inf. Syst. 65(5): 2281-2304 (2023) - [j123]Yuecen Wei, Xingcheng Fu, Dongqi Yan, Qingyun Sun, Hao Peng, Jia Wu, Jinyan Wang, Xianxian Li:
Heterogeneous graph neural network with semantic-aware differential privacy guarantees. Knowl. Inf. Syst. 65(10): 4085-4110 (2023) - [j122]Rong Gao, Yuhe Tao, Yonghong Yu, Jia Wu, Xiongkai Shao, Jing Li, Zhiwei Ye:
Self-supervised Dual Hypergraph learning with Intent Disentanglement for session-based recommendation. Knowl. Based Syst. 270: 110528 (2023) - [j121]Qi Huang, Chuan Zhou, Jia Wu, Luchen Liu, Bin Wang:
Deep spatial-temporal structure learning for rumor detection on Twitter. Neural Comput. Appl. 35(18): 12995-13005 (2023) - [j120]Chenyan Zhang, Shan Xue, Jing Li, Jia Wu, Bo Du, Donghua Liu, Jun Chang:
Multi-Aspect enhanced Graph Neural Networks for recommendation. Neural Networks 157: 90-102 (2023) - [j119]Yunbo Tang, Dan Chen, Jia Wu, Weiping Tu, Jessica J. M. Monaghan, Paul F. Sowman, David McAlpine:
Functional connectivity learning via Siamese-based SPD matrix representation of brain imaging data. Neural Networks 163: 272-285 (2023) - [j118]Yunbo Tang, Dan Chen, Jia Wu, Weiping Tu, Jessica J. M. Monaghan, Paul F. Sowman, David McAlpine:
Corrigendum to "Functional Connectivity Learning via Siamese-based SPD Matrix Representation of Brain Imaging Data" [Neural Networks 163 (2023) 272-285]. Neural Networks 164: 575 (2023) - [j117]Jin Fan, Zehao Wang, Huifeng Wu, Danfeng Sun, Jia Wu, Xin Lu:
An Adversarial Time-Frequency Reconstruction Network for Unsupervised Anomaly Detection. Neural Networks 168: 44-56 (2023) - [j116]Wenhang Yu, Xueqi Ma, James Bailey, Yibing Zhan, Jia Wu, Bo Du, Wenbin Hu:
Graph structure reforming framework enhanced by commute time distance for graph classification. Neural Networks 168: 539-548 (2023) - [j115]Jianxin Li, Qingyun Sun, Hao Peng, Beining Yang, Jia Wu, Philip S. Yu:
Adaptive Subgraph Neural Network With Reinforced Critical Structure Mining. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8063-8080 (2023) - [j114]Xixun Lin, Chuan Zhou, Jia Wu, Hong Yang, Haibo Wang, Yanan Cao, Bin Wang:
Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node Classification. Pattern Recognit. 133: 109042 (2023) - [j113]Wenchao Weng, Jin Fan, Huifeng Wu, Yujie Hu, Hao Tian, Fu Zhu, Jia Wu:
A Decomposition Dynamic graph convolutional recurrent network for traffic forecasting. Pattern Recognit. 142: 109670 (2023) - [j112]Tarique Anwar, Surya Nepal, Cécile Paris, Jian Yang, Jia Wu, Quan Z. Sheng:
Tracking the Evolution of Clusters in Social Media Streams. IEEE Trans. Big Data 9(2): 701-715 (2023) - [j111]Pengbo Li, Hang Yu, Xiangfeng Luo, Jia Wu:
LGM-GNN: A Local and Global Aware Memory-Based Graph Neural Network for Fraud Detection. IEEE Trans. Big Data 9(4): 1116-1127 (2023) - [j110]Weichao Liang, Jie Cao, Lei Chen, Youquan Wang, Jia Wu, Amin Beheshti, Jiangnan Tang:
Crime Prediction With Missing Data Via Spatiotemporal Regularized Tensor Decomposition. IEEE Trans. Big Data 9(5): 1392-1407 (2023) - [j109]Qian Li, Shu Guo, Jia Wu, Jianxin Li, Jiawei Sheng, Hao Peng, Lihong Wang:
Event Extraction by Associating Event Types and Argument Roles. IEEE Trans. Big Data 9(6): 1549-1560 (2023) - [j108]Xiaosai Huang, Jing Li, Jia Wu, Jun Chang, Donghua Liu:
Transfer Learning With Document-Level Data Augmentation for Aspect-Level Sentiment Classification. IEEE Trans. Big Data 9(6): 1643-1657 (2023) - [j107]Guanghui Li, Jiahua Shen, Chenglong Dai, Jia Wu, Stefanie I. Becker:
ShVEEGc: EEG Clustering With Improved Cosine Similarity-Transformed Shapley Value. IEEE Trans. Emerg. Top. Comput. Intell. 7(1): 222-236 (2023) - [j106]Beihang Song, Jing Li, Jia Wu, Bo Du, Jun Chang, Jun Wan, Tianpeng Liu:
SRDF: Single-Stage Rotate Object Detector via Dense Prediction and False Positive Suppression. IEEE Trans. Geosci. Remote. Sens. 61: 1-16 (2023) - [j105]Tong Liu, Jing Li, Jia Wu, Bo Du, Jun Chang, Yi Liu:
Facial Expression Recognition on the High Aggregation Subgraphs. IEEE Trans. Image Process. 32: 3732-3745 (2023) - [j104]Lei Chen, Jie Cao, Haicheng Tao, Jia Wu:
Trip Reinforcement Recommendation with Graph-based Representation Learning. ACM Trans. Knowl. Discov. Data 17(4): 57:1-57:20 (2023) - [j103]Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Dongxiao He, Jia Wu, Philip S. Yu, Weixiong Zhang:
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning. IEEE Trans. Knowl. Data Eng. 35(2): 1149-1170 (2023) - [j102]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Yang Yang, Philip S. Yu:
Signed Network Representation by Preserving Multi-Order Signed Proximity. IEEE Trans. Knowl. Data Eng. 35(3): 3087-3100 (2023) - [j101]Zhenyu Qiu, Jia Wu, Wenbin Hu, Bo Du, Guocai Yuan, Philip S. Yu:
Temporal Link Prediction With Motifs for Social Networks. IEEE Trans. Knowl. Data Eng. 35(3): 3145-3158 (2023) - [j100]Xusheng Zhao, Qiong Dai, Jia Wu, Hao Peng, Mingsheng Liu, Xu Bai, Jianlong Tan, Senzhang Wang, Philip S. Yu:
Multi-View Tensor Graph Neural Networks Through Reinforced Aggregation. IEEE Trans. Knowl. Data Eng. 35(4): 4077-4091 (2023) - [j99]Chenglong Dai, Jia Wu, Jessica J. M. Monaghan, Guanghui Li, Hao Peng, Stefanie I. Becker, David McAlpine:
Semi-Supervised EEG Clustering With Multiple Constraints. IEEE Trans. Knowl. Data Eng. 35(8): 8529-8544 (2023) - [j98]Yuyao Wang, Jie Cao, Zhan Bu, Jia Wu, Youquan Wang:
Dual Structural Consistency Preserving Community Detection on Social Networks. IEEE Trans. Knowl. Data Eng. 35(11): 11301-11315 (2023) - [j97]Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Chuan Zhou, Quan Z. Sheng, Hui Xiong, Leman Akoglu:
A Comprehensive Survey on Graph Anomaly Detection With Deep Learning. IEEE Trans. Knowl. Data Eng. 35(12): 12012-12038 (2023) - [j96]Tianpeng Liu, Jing Li, Jia Wu, Jun Chang, Beihang Song, Bowen Yao:
Tracking With Mutual Attention Network. IEEE Trans. Multim. 25: 5330-5343 (2023) - [j95]Sanmin Liu, Shan Xue, Jia Wu, Chuan Zhou, Jian Yang, Zhao Li, Jie Cao:
Online Active Learning for Drifting Data Streams. IEEE Trans. Neural Networks Learn. Syst. 34(1): 186-200 (2023) - [j94]Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Shan Xue, Qianli Xing, Philip S. Yu:
C-DeepTrust: A Context-Aware Deep Trust Prediction Model in Online Social Networks. IEEE Trans. Neural Networks Learn. Syst. 34(6): 2767-2780 (2023) - [j93]Danfeng Sun, Jianyong Zhao, Baiping Chen, Huifeng Wu, Jia Wu:
Cross-Level Dependability Assessment With a Distributed Split Mechanism for Wireless Communication Systems. IEEE Trans. Netw. Sci. Eng. 10(5): 2832-2842 (2023) - [j92]Lei Chen, Jie Cao, Weichao Liang, Jia Wu, Qiaolin Ye:
Keywords-enhanced Deep Reinforcement Learning Model for Travel Recommendation. ACM Trans. Web 17(1): 5:1-5:21 (2023) - [j91]Hao Peng, Jian Yang, Jia Wu, Philip S. Yu:
Introduction to the Special Issue on Advanced Graph Mining on the Web: Theory, Algorithms, and Applications: Part 1. ACM Trans. Web 17(3): 14:1-14:2 (2023) - [j90]Youquan Wang, Zhiwen Dai, Jie Cao, Jia Wu, Haicheng Tao, Guixiang Zhu:
Intra- and inter-association attention network-enhanced policy learning for social group recommendation. World Wide Web (WWW) 26(1): 71-94 (2023) - [j89]Zhenchang Xia, Libing Wu, Fei Wang, Xudong Liao, Haiyan Hu, Jia Wu, Dan Wu:
Glider: rethinking congestion control with deep reinforcement learning. World Wide Web (WWW) 26(1): 115-137 (2023) - [j88]Yufei Liu, Jie Cao, Jia Wu, Dechang Pi:
Modeling the social influence of COVID-19 via personalized propagation with deep learning. World Wide Web (WWW) 26(4): 2075-2097 (2023) - 2022
- [j87]Shuqin Cao, Libing Wu, Jia Wu, Dan Wu, Qingan Li:
A spatio-temporal sequence-to-sequence network for traffic flow prediction. Inf. Sci. 610: 185-203 (2022) - [j86]Yutong Qu, Wei Emma Zhang, Jian Yang, Lingfei Wu, Jia Wu:
Knowledge-aware document summarization: A survey of knowledge, embedding methods and architectures. Knowl. Based Syst. 257: 109882 (2022) - [j85]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu:
Signed network representation with novel node proximity evaluation. Neural Networks 148: 142-154 (2022) - [j84]Bowen Yao, Jing Li, Shan Xue, Jia Wu, Huanmei Guan, Jun Chang, Zhiquan Ding:
GARAT: Generative Adversarial Learning for Robust and Accurate Tracking. Neural Networks 148: 206-218 (2022) - [j83]Xusheng Zhao, Jia Wu, Hao Peng, Amin Beheshti, Jessica J. M. Monaghan, David McAlpine, Heivet Hernandez-Perez, Mark Dras, Qiong Dai, Yangyang Li, Philip S. Yu, Lifang He:
Deep reinforcement learning guided graph neural networks for brain network analysis. Neural Networks 154: 56-67 (2022) - [j82]Jinyan Ma, Jing Li, Bo Du, Jia Wu, Jun Wan, Yafu Xiao:
Robust face alignment by dual-attentional spatial-aware capsule networks. Pattern Recognit. 122: 108297 (2022) - [j81]Qian Li, Hao Peng, Jianxin Li, Jia Wu, Yuanxing Ning, Lihong Wang, Philip S. Yu, Zheng Wang:
Reinforcement Learning-Based Dialogue Guided Event Extraction to Exploit Argument Relations. IEEE ACM Trans. Audio Speech Lang. Process. 30: 520-533 (2022) - [j80]Chenglong Dai, Jia Wu, Dechang Pi, Stefanie I. Becker, Lin Cui, Qin Zhang, Blake W. Johnson:
Brain EEG Time-Series Clustering Using Maximum-Weight Clique. IEEE Trans. Cybern. 52(1): 357-371 (2022) - [j79]Chenyan Zhang, Jing Li, Jia Wu, Donghua Liu, Jun Chang, Rong Gao:
Deep Recommendation With Adversarial Training. IEEE Trans. Emerg. Top. Comput. 10(4): 1966-1978 (2022) - [j78]Qin Li, Jia Wu, Junyu Quan, Jinjing Shi, Shichao Zhang:
Efficient Quantum Blockchain With a Consensus Mechanism QDPoS. IEEE Trans. Inf. Forensics Secur. 17: 3264-3276 (2022) - [j77]Danfeng Sun, Shan Xue, Huifeng Wu, Jia Wu:
A Data Stream Cleaning System Using Edge Intelligence for Smart City Industrial Environments. IEEE Trans. Ind. Informatics 18(2): 1165-1174 (2022) - [j76]Donghua Liu, Jia Wu, Jing Li, Bo Du, Jun Chang, Xuefei Li:
Adaptive Hierarchical Attention-Enhanced Gated Network Integrating Reviews for Item Recommendation. IEEE Trans. Knowl. Data Eng. 34(5): 2076-2090 (2022) - [j75]Chenglong Dai, Jia Wu, Dechang Pi, Lin Cui, Blake W. Johnson, Stefanie I. Becker:
Electroencephalogram Signal Clustering With Convex Cooperative Games. IEEE Trans. Knowl. Data Eng. 34(12): 5755-5769 (2022) - [j74]Zhongze Chen, Jing Li, Jia Wu, Jun Chang, Yafu Xiao, Xiaoting Wang:
Drift-Proof Tracking With Deep Reinforcement Learning. IEEE Trans. Multim. 24: 609-624 (2022) - [j73]Xiaoxiao Ma, Shan Xue, Jia Wu, Jian Yang, Cécile Paris, Surya Nepal, Quan Z. Sheng:
Deep Multi-Attributed-View Graph Representation Learning. IEEE Trans. Netw. Sci. Eng. 9(5): 3762-3774 (2022) - [j72]Ge Zhang, Zhao Li, Jiaming Huang, Jia Wu, Chuan Zhou, Jian Yang, Jianliang Gao:
eFraudCom: An E-commerce Fraud Detection System via Competitive Graph Neural Networks. ACM Trans. Inf. Syst. 40(3): 47:1-47:29 (2022) - [j71]Fanzhen Liu, Zhao Li, Baokun Wang, Jia Wu, Jian Yang, Jiaming Huang, Yiqing Zhang, Weiqiang Wang, Shan Xue, Surya Nepal, Quan Z. Sheng:
eRiskCom: an e-commerce risky community detection platform. VLDB J. 31(5): 1085-1101 (2022) - 2021
- [j70]Peiyao Li, Weiliang Zhao, Jian Yang, Jia Wu:
CoTrRank: Trust Ranking on Twitter. IEEE Intell. Syst. 36(1): 35-45 (2021) - [j69]Wanchun Jiang, Haoyang Li, Lijuan Peng, Jia Wu, Chang Ruan, Jianxin Wang:
Analysis and improvement of the latency-based congestion control algorithm DX. Future Gener. Comput. Syst. 123: 206-218 (2021) - [j68]Xiaoqian Yue, Jing Li, Jia Wu, Jun Chang, Jun Wan, Jinyan Ma:
Multi-task adversarial autoencoder network for face alignment in the wild. Neurocomputing 437: 261-273 (2021) - [j67]Zhen Zhang, Jiajun Bu, Zhao Li, Chengwei Yao, Can Wang, Jia Wu:
TigeCMN: On exploration of temporal interaction graph embedding via Coupled Memory Neural Networks. Neural Networks 140: 13-26 (2021) - [j66]Chuang Liu, Jia Wu, Weiwei Liu, Wenbin Hu:
Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information. Neural Networks 142: 20-33 (2021) - [j65]Zhenchang Xia, Shan Xue, Jia Wu, Yanjiao Chen, Junjie Chen, Libing Wu:
Deep Reinforcement Learning for Smart City Communication Networks. IEEE Trans. Ind. Informatics 17(6): 4188-4196 (2021) - [j64]Zhenchang Xia, Jia Wu, Libing Wu, Yanjiao Chen, Jian Yang, Philip S. Yu:
A Comprehensive Survey of the Key Technologies and Challenges Surrounding Vehicular Ad Hoc Networks. ACM Trans. Intell. Syst. Technol. 12(4): 37:1-37:30 (2021) - [j63]Danfeng Sun, Jia Wu, Jian Yang, Huifeng Wu:
Intelligent Data Collaboration in Heterogeneous-device IoT Platforms. ACM Trans. Sens. Networks 17(3): 22:1-22:17 (2021) - [j62]Naime Ranjbar Kermany, Weiliang Zhao, Jian Yang, Jia Wu, Luiz Pizzato:
A fairness-aware multi-stakeholder recommender system. World Wide Web 24(6): 1995-2018 (2021) - 2020
- [j61]Yongqiang Zhao, Shirui Pan, Jia Wu, Huaiyu Wan, Huizhi Liang, Haishuai Wang, Huawei Shen:
IEEE Access Special Section Editorial: Advanced Data Mining Methods for Social Computing. IEEE Access 8: 228598-228604 (2020) - [j60]Sanmin Liu, Shan Xue, Fanzhen Liu, Jieren Cheng, Xiulai Li, Chao Kong, Jia Wu:
Microcluster-Based Incremental Ensemble Learning for Noisy, Nonstationary Data Streams. Complex. 2020: 6147378:1-6147378:12 (2020) - [j59]Yujia Wu, Jing Li, Jia Wu, Jun Chang:
Siamese capsule networks with global and local features for text classification. Neurocomputing 390: 88-98 (2020) - [j58]Jiayi Ma, Pengwei Liang, Wei Yu, Chen Chen, Xiaojie Guo, Jia Wu, Junjun Jiang:
Infrared and visible image fusion via detail preserving adversarial learning. Inf. Fusion 54: 85-98 (2020) - [j57]Huifeng Wu, Danfeng Sun, Lan Peng, Yuan Yao, Jia Wu, Quan Z. Sheng, Yi Yan:
Dynamic Edge Access System in IoT Environment. IEEE Internet Things J. 7(4): 2509-2520 (2020) - [j56]Yafu Xiao, Jing Li, Bo Du, Jia Wu, Jun Chang, Wenfan Zhang:
MeMu: Metric correlation Siamese network and multi-class negative sampling for visual tracking. Pattern Recognit. 100: 107170 (2020) - [j55]Chenglong Dai, Dechang Pi, Stefanie I. Becker, Jia Wu, Lin Cui, Blake W. Johnson:
CenEEGs: Valid EEG Selection for Classification. ACM Trans. Knowl. Discov. Data 14(2): 18:1-18:25 (2020) - [j54]Yongshan Zhang, Jia Wu, Zhihua Cai, Philip S. Yu:
Multi-View Multi-Label Learning With Sparse Feature Selection for Image Annotation. IEEE Trans. Multim. 22(11): 2844-2857 (2020) - [j53]Lin Cui, Jia Wu, Dechang Pi, Peng Zhang, Paul J. Kennedy:
Dual Implicit Mining-Based Latent Friend Recommendation. IEEE Trans. Syst. Man Cybern. Syst. 50(5): 1663-1678 (2020) - [j52]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) - [j51]Guojia Wan, Bo Du, Shirui Pan, Jia Wu:
Adaptive knowledge subgraph ensemble for robust and trustworthy knowledge graph completion. World Wide Web 23(1): 471-490 (2020) - [j50]Fanzhen Liu, Jia Wu, Shan Xue, Chuan Zhou, Jian Yang, Quanzheng Sheng:
Detecting the evolving community structure in dynamic social networks. World Wide Web 23(2): 715-733 (2020) - [j49]Peiyao Li, Weiliang Zhao, Jian Yang, Quan Z. Sheng, Jia Wu:
Let's CoRank: trust of users and tweets on social networks. World Wide Web 23(5): 2877-2901 (2020) - 2019
- [j48]Jia Wu, Shirui Pan, Junjun Jiang, Zhihua Cai, Bo Du, Yingjie Tian, Shuaiqiang Wang, Haishuai Wang:
IEEE Access Special Section Editorial: Advanced Data Analytics for Large-Scale Complex Data Environments. IEEE Access 7: 33778-33786 (2019) - [j47]Qing Wu, Jie Wang, Jin Fan, Gang Xu, Jia Wu, Blake W. Johnson, Xingfei Li, Quan Do, Ruiquan Ge:
Improved Coupled Tensor Factorization with Its Applications in Health Data Analysis. Complex. 2019: 1574240:1-1574240:16 (2019) - [j46]Jian Jiang, Fei Lin, Jin Fan, Hang Lv, Jia Wu:
A Destination Prediction Network Based on Spatiotemporal Data for Bike-Sharing. Complex. 2019: 7643905:1-7643905:14 (2019) - [j45]Yafu Xiao, Jing Li, Bo Du, Jia Wu, Xuefei Li, Jun Chang, Yifei Zhou:
Robust correlation filter tracking with multi-scale spatial view. Neurocomputing 358: 119-140 (2019) - [j44]Yongshan Zhang, Jia Wu, Zhihua Cai, Bo Du, Philip S. Yu:
An unsupervised parameter learning model for RVFL neural network. Neural Networks 112: 85-97 (2019) - [j43]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) - [j42]Haishuai Wang, Qin Zhang, Jia Wu, Shirui Pan, Yixin Chen:
Time series feature learning with labeled and unlabeled data. Pattern Recognit. 89: 55-66 (2019) - [j41]Haishuai Wang, Jia Wu, Peng Zhang, Yixin Chen:
Learning Shapelet Patterns from Network-Based Time Series. IEEE Trans. Ind. Informatics 15(7): 3864-3876 (2019) - [j40]Yongshan Zhang, Jia Wu, Chuan Zhou, Zhihua Cai, Jian Yang, Philip S. Yu:
Multi-View Fusion with Extreme Learning Machine for Clustering. ACM Trans. Intell. Syst. Technol. 10(5): 53:1-53:23 (2019) - [j39]Huan Wang, Jia Wu, Wenbin Hu, Xindong Wu:
Detecting and Assessing Anomalous Evolutionary Behaviors of Nodes in Evolving Social Networks. ACM Trans. Knowl. Discov. Data 13(1): 12:1-12:24 (2019) - [j38]Liangxiao Jiang, Lungan Zhang, Chaoqun Li, Jia Wu:
A Correlation-Based Feature Weighting Filter for Naive Bayes. IEEE Trans. Knowl. Data Eng. 31(2): 201-213 (2019) - [j37]Jiayi Ma, Jia Wu, Ji Zhao, Junjun Jiang, Huabing Zhou, Quan Z. Sheng:
Nonrigid Point Set Registration With Robust Transformation Learning Under Manifold Regularization. IEEE Trans. Neural Networks Learn. Syst. 30(12): 3584-3597 (2019) - 2018
- [j36]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) - [j35]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) - [j34]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) - [j33]Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu:
A Novel Consistent Random Forest Framework: Bernoulli Random Forests. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3510-3523 (2018) - [j32]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) - 2017
- [j31]Haishuai Wang, Jia Wu, Shirui Pan, Peng Zhang, Ling Chen:
Towards large-scale social networks with online diffusion provenance detection. Comput. Networks 114: 154-166 (2017) - [j30]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) - [j29]Yisen Wang, Fangbing Liu, Shu-Tao Xia, Jia Wu:
Link sign prediction by Variational Bayesian Probabilistic Matrix Factorization with Student-t Prior. Inf. Sci. 405: 175-189 (2017) - [j28]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Boosting for graph classification with universum. Knowl. Inf. Syst. 50(1): 53-77 (2017) - [j27]Chaoqun Li, Liangxiao Jiang, Hongwei Li, Jia Wu, Peng Zhang:
Toward value difference metric with attribute weighting. Knowl. Inf. Syst. 50(3): 795-825 (2017) - [j26]Yisen Wang, Shu-Tao Xia, Jia Wu:
A less-greedy two-term Tsallis Entropy Information Metric approach for decision tree classification. Knowl. Based Syst. 120: 34-42 (2017) - [j25]Yongshan Zhang, Jia Wu, Chuan Zhou, Zhihua Cai:
Instance cloned extreme learning machine. Pattern Recognit. 68: 52-65 (2017) - [j24]Dongkuan Xu, Jia Wu, Dewei Li, Yingjie Tian, Xingquan Zhu, Xindong Wu:
SALE: Self-adaptive LSH encoding for multi-instance learning. Pattern Recognit. 71: 460-482 (2017) - [j23]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) - [j22]Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Xindong Wu:
Positive and Unlabeled Multi-Graph Learning. IEEE Trans. Cybern. 47(4): 818-829 (2017) - [j21]Bo Du, Wei Xiong, Jia Wu, Lefei Zhang, Liangpei Zhang, Dacheng Tao:
Stacked Convolutional Denoising Auto-Encoders for Feature Representation. IEEE Trans. Cybern. 47(4): 1017-1027 (2017) - [j20]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) - 2016
- [j19]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) - [j18]Weixue Lu, Chuan Zhou, Jia Wu:
Big social network influence maximization via recursively estimating influence spread. Knowl. Based Syst. 113: 143-154 (2016) - [j17]Jia Wu, Shirui Pan, Xingquan Zhu, Peng Zhang, Chengqi Zhang:
SODE: Self-Adaptive One-Dependence Estimators for classification. Pattern Recognit. 51: 358-377 (2016) - [j16]Yongshan Zhang, Jia Wu, Zhihua Cai, Peng Zhang, Ling Chen:
Memetic Extreme Learning Machine. Pattern Recognit. 58: 135-148 (2016) - [j15]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) - 2015
- [j14]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) - [j13]Jia Wu, Bi Wu, Shirui Pan, Haishuai Wang, Zhihua Cai:
Locally Weighted Learning: How and When Does it Work in Bayesian Networks? Int. J. Comput. Intell. Syst. 8(sup1): 63-74 (2015) - [j12]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) - [j11]Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai:
Boosting for Multi-Graph Classification. IEEE Trans. Cybern. 45(3): 430-443 (2015) - [j10]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) - [j9]Shirui Pan, Jia Wu, Xingquan Zhu:
CogBoost: Boosting for Fast Cost-Sensitive Graph Classification. IEEE Trans. Knowl. Data Eng. 27(11): 2933-2946 (2015) - 2014
- [j8]Jia Wu, Zhihua Cai:
Learning attribute weighted AODE for ROC area ranking. Int. J. Inf. Commun. Technol. 6(1): 23-38 (2014) - [j7]Jia Wu, Zhihua Cai:
A naive Bayes probability estimation model based on self-adaptive differential evolution. J. Intell. Inf. Syst. 42(3): 671-694 (2014) - [j6]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) - 2013
- [j5]Jia Wu, Zhihua Cai, Xiaolin Chen, Shuang Ao:
Active AODE learning based on a novel sampling strategy and its application. Int. J. Comput. Appl. Technol. 47(4): 326-333 (2013) - [j4]Jia Wu, Zhihua Cai:
Boosting for superparent-one-dependence estimators. Int. J. Comput. Sci. Math. 4(3): 277-286 (2013) - [j3]Jia Wu, Zhihua Cai, Xiaolin Chen, Meng Li, Bin Guo:
Weighted Clone Selection Algorithm based on Rough Set Theory. J. Softw. 8(6): 1333-1338 (2013) - 2012
- [j2]Jia Wu, Zhihua Cai, Shuang Ao:
Hybrid dynamic k-nearest-neighbour and distance and attribute weighted method for classification. Int. J. Comput. Appl. Technol. 43(4): 378-384 (2012) - [j1]Jia Wu, Zhihua Cai, Xiaolin Chen, Shuang Ao, Yongshan Zhang:
Attribute Weighting via Differential Evolution for Attribute Weighted Clonal Selection Algorithm. J. Comput. 7(12): 3013-3019 (2012)
Conference and Workshop Papers
- 2024
- [c128]Nasrin Shabani, Amin Beheshti, Jia Wu, Maryam Khanian Najafabadi, Jin Foo, Alireza Jolfaei:
GraphSUM: Scalable Graph Summarization for Efficient Question Answering. EDBT 2024: 794-797 - [c127]Xuexiong Luo, Guangwei Dong, Jia Wu, Amin Beheshti, Jian Yang, Shan Xue:
An Interpretable Brain Graph Contrastive Learning Framework for Brain Disorder Analysis. WSDM 2024: 1074-1077 - 2023
- [c126]Fu Lin, Xuexiong Luo, Jia Wu, Jian Yang, Shan Xue, Zitong Wang, Haonan Gong:
Discriminative Graph-Level Anomaly Detection via Dual-Students-Teacher Model. ADMA (3) 2023: 261-276 - [c125]Yuchen Zhang, Xing Su, Jia Wu, Jian Yang, Hao Fan, Xiaochuan Zheng:
EmoKnow: Emotion- and Knowledge-Oriented Model for COVID-19 Fake News Detection. ADMA (1) 2023: 352-367 - [c124]Yongsheng Yu, Jia Wu, Jian Yang:
Social Event Detection with Reinforced Deep Heterogeneous Graph Attention Network. IEEE Big Data 2023: 463-472 - [c123]Zepeng Wang, Xiaochuan Shi, Chao Ma, Libing Wu, Jia Wu:
CCPO: Conservatively Constrained Policy Optimization Using State Augmentation. ECAI 2023: 2599-2606 - [c122]Li Zheng, Zhao Li, Jun Gao, Zhenpeng Li, Jia Wu, Chuan Zhou:
Domain Adaptation for Anomaly Detection on Heterogeneous Graphs in E-Commerce. ECIR (2) 2023: 304-318 - [c121]Tong Liu, Jing Li, Jia Wu, Lefei Zhang, Shanshan Zhao, Jun Chang, Jun Wan:
Cross-Domain Facial Expression Recognition via Disentangling Identity Representation. IJCAI 2023: 1213-1221 - [c120]Yilong Zang, Ruimin Hu, Zheng Wang, Danni Xu, Jia Wu, Dengshi Li, Junhang Wu, Lingfei Ren:
Don't Ignore Alienation and Marginalization: Correlating Fraud Detection. IJCAI 2023: 4959-4966 - [c119]Chuang Liu, Yibing Zhan, Jia Wu, Chang Li, Bo Du, Wenbin Hu, Tongliang Liu, Dacheng Tao:
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities. IJCAI 2023: 6712-6722 - [c118]Jinhua Chen, Jin Fan, Zhen Liu, Jiaqian Xiang, Jia Wu:
Segformer: Segment-Based Transformer with Decomposition for Long-Term Series Forecasting. IJCNN 2023: 1-8 - [c117]Jin Fan, Zhanyu Si, Zehao Wang, Danfeng Sun, Jia Wu, Huifeng Wu:
OOA-UADS: Offline, Online, Analysis-an Unsupervised Anomaly Detection Solution for Multivariate Time Series. IJCNN 2023: 1-9 - [c116]Yuchen Zhang, Yifan Wang, Hao Fan, Jing Li, Jia Wu:
Worldwide COVID-19 Topic Knowledge Graph Analysis From Social Media. IJCNN 2023: 1-10 - [c115]Xiaoxiao Ma, Jia Wu, Jian Yang, Quan Z. Sheng:
Towards Graph-level Anomaly Detection via Deep Evolutionary Mapping. KDD 2023: 1631-1642 - [c114]Bingbing Xie, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Hao Fan:
Heterogeneous Graph Neural Network via Knowledge Relations for Fake News Detection. SSDBM 2023: 15:1-15:11 - [c113]Hongjiao Liu, Shan Xue, Jian Yang, Jia Wu:
Enhancing Trust Prediction in Attributed Social Networks with Self-Supervised Learning. WISE 2023: 160-175 - [c112]Xing Su, Jian Yang, Jia Wu, Yuchen Zhang:
Mining User-aware Multi-relations for Fake News Detection in Large Scale Online Social Networks. WSDM 2023: 51-59 - [c111]Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Hao Peng, Angsheng Li, Shan Xue, Jianlin Su:
Minimum Entropy Principle Guided Graph Neural Networks. WSDM 2023: 114-122 - [c110]Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu:
Unbiased and Efficient Self-Supervised Incremental Contrastive Learning. WSDM 2023: 922-930 - [c109]Yang Liu, Chuan Zhou, Shirui Pan, Jia Wu, Zhao Li, Hongyang Chen, Peng Zhang:
CurvDrop: A Ricci Curvature Based Approach to Prevent Graph Neural Networks from Over-Smoothing and Over-Squashing. WWW 2023: 221-230 - [c108]Xingcheng Fu, Yuecen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li:
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification. WWW 2023: 460-468 - [c107]Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu:
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization. WWW 2023: 499-510 - [c106]Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu:
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks. WWW 2023: 727-736 - 2022
- [c105]Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu:
Graph Structure Learning with Variational Information Bottleneck. AAAI 2022: 4165-4174 - [c104]Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu:
Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees. CIKM 2022: 1685-1695 - [c103]Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He:
From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection. CIKM 2022: 1696-1705 - [c102]Ruitong Zhang, Hao Peng, Yingtong Dou, Jia Wu, Qingyun Sun, Yangyang Li, Jingyi Zhang, Philip S. Yu:
Automating DBSCAN via Deep Reinforcement Learning. CIKM 2022: 2620-2630 - [c101]Fanzhen Liu, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu C. Aggarwal:
DAGAD: Data Augmentation for Graph Anomaly Detection. ICDM 2022: 259-268 - [c100]Qianren Mao, Yiming Wang, Chenghong Yang, Linfeng Du, Hao Peng, Jia Wu, Jianxin Li, Zheng Wang:
HiGIL: Hierarchical Graph Inference Learning for Fact Checking. ICDM 2022: 329-337 - [c99]Yuecen Wei, Xingcheng Fu, Qingyun Sun, Hao Peng, Jia Wu, Jinyan Wang, Xianxian Li:
Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation. ICDM 2022: 528-537 - [c98]Naime Ranjbar Kermany, Luiz Pizzato, Jian Yang, Shan Xue, Jia Wu:
PD-SRS: Personalized Diversity for a Fair Session-Based Recommendation System. ICSOC 2022: 331-339 - [c97]Jiaqian Ren, Lei Jiang, Hao Peng, Zhiwei Liu, Jia Wu, Philip S. Yu:
Evidential Temporal-aware Graph-based Social Event Detection via Dempster-Shafer Theory. ICWS 2022: 331-336 - [c96]Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng:
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification. IJCAI 2022: 1959-1965 - [c95]Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal:
Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection. NeurIPS 2022 - [c94]Xuexiong Luo, Jia Wu, Amin Beheshti, Jian Yang, Xiankun Zhang, Yuan Wang, Shan Xue:
ComGA: Community-Aware Attributed Graph Anomaly Detection. WSDM 2022: 657-665 - [c93]Naime Ranjbar Kermany, Jian Yang, Jia Wu, Luiz Pizzato:
Fair-SRS: A Fair Session-based Recommendation System. WSDM 2022: 1601-1604 - [c92]Fengzhao Shi, Yanan Cao, Yanmin Shang, Yuchen Zhou, Chuan Zhou, Jia Wu:
H2-FDetector: A GNN-based Fraud Detector with Homophilic and Heterophilic Connections. WWW 2022: 1486-1494 - [c91]Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng:
Curvature Graph Generative Adversarial Networks. WWW 2022: 1528-1537 - [c90]Pinghua Xu, Yibing Zhan, Liu Liu, Baosheng Yu, Bo Du, Jia Wu, Wenbin Hu:
Dual-branch Density Ratio Estimation for Signed Network Embedding. WWW 2022: 1651-1662 - 2021
- [c89]Libing Wu, Min Wang, Dan Wu, Jia Wu:
DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control. CIKM 2021: 2150-2159 - [c88]Chen Li, Xutan Peng, Hao Peng, Jia Wu, Lihong Wang, Philip S. Yu, Jianxin Li, Lichao Sun:
Graph-based Semi-Supervised Learning by Strengthening Local Label Consistency. CIKM 2021: 3201-3205 - [c87]Xingcheng Fu, Jianxin Li, Jia Wu, Qingyun Sun, Cheng Ji, Senzhang Wang, Jiajun Tan, Hao Peng, Philip S. Yu:
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network. ICDM 2021: 111-120 - [c86]Xixun Lin, Jiangxia Cao, Peng Zhang, Chuan Zhou, Zhao Li, Jia Wu, Bin Wang:
Disentangled Deep Multivariate Hawkes Process for Learning Event Sequences. ICDM 2021: 360-369 - [c85]Ge Zhang, Jia Wu, Jian Yang, Amin Beheshti, Shan Xue, Chuan Zhou, Quan Z. Sheng:
FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and Imbalance. ICDM 2021: 867-876 - [c84]Qianli Xing, Weiliang Zhao, Jian Yang, Jia Wu, Qi Wang:
TWLR: A Novel Truth Inference Approach based on Worker Representations for Crowdsourcing in the Low Redundancy Situation. ICWS 2021: 79-86 - [c83]Qianli Xing, Weiliang Zhao, Jian Yang, Jia Wu, Qi Wang:
WorP: A Novel Worker Performance Prediction Model for General Tasks on Crowdsourcing Platforms. ICWS 2021: 161-166 - [c82]Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan, Yanan Cao, Bin Wang:
Task-adaptive Neural Process for User Cold-Start Recommendation. WWW 2021: 1306-1316 - [c81]Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Yuanxing Ning, Philip S. Yu, Lifang He:
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. WWW 2021: 2081-2091 - [c80]Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, Philip S. Yu:
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs. WWW 2021: 3383-3395 - 2020
- [c79]Yang Guo, Weiliang Zhao, Jian Yang, Zizhu Zhang, Jia Wu, Tarique Anwar:
FDA-VeD: A Future-Demand-Aware Vehicle Dispatching Service. SCC 2020: 345-352 - [c78]Naime Ranjbar Kermany, Weiliang Zhao, Jian Yang, Jia Wu, Luiz Pizzato:
An Ethical Multi-Stakeholder Recommender System Based on Evolutionary Multi-Objective Optimization. SCC 2020: 478-480 - [c77]Zhenyu Qiu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Xiaohua Jia:
Temporal Network Embedding with High-Order Nonlinear Information. AAAI 2020: 5436-5443 - [c76]Qiannan Zhu, Xiaofei Zhou, Jia Wu, Jianlong Tan, Li Guo:
A Knowledge-Aware Attentional Reasoning Network for Recommendation. AAAI 2020: 6999-7006 - [c75]Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Chuan Zhou, Qianli Xing:
AtNE-Trust: Attributed Trust Network Embedding for Trust Prediction in Online Social Networks. ICDM 2020: 601-610 - [c74]Xixun Lin, Chuan Zhou, Hong Yang, Jia Wu, Haibo Wang, Yanan Cao, Bin Wang:
Exploratory Adversarial Attacks on Graph Neural Networks. ICDM 2020: 1136-1141 - [c73]Xuexiong Luo, Jia Wu, Chuan Zhou, Xiankun Zhang, Yuan Wang:
Deep Semantic Network Representation. ICDM 2020: 1154-1159 - [c72]Qianli Xing, Weiliang Zhao, Jian Yang, Jia Wu, Qi Wang:
PB-Worker: A Novel Participating Behavior-based Worker Ability Model for General Tasks on Crowdsourcing Platforms. ICWS 2020: 37-44 - [c71]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu:
Opinion Maximization in Social Trust Networks. IJCAI 2020: 1251-1257 - [c70]Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Jian Yang, Philip S. Yu:
Deep Learning for Community Detection: Progress, Challenges and Opportunities. IJCAI 2020: 4981-4987 - [c69]Qi Huang, Junshuai Yu, Jia Wu, Bin Wang:
Heterogeneous Graph Attention Networks for Early Detection of Rumors on Twitter. IJCNN 2020: 1-8 - [c68]Yipeng Zhang, Bo Du, Lefei Zhang, Jia Wu:
Parallel DNN Inference Framework Leveraging a Compact RISC-V ISA-based Multi-core System. KDD 2020: 627-635 - [c67]Yang Guo, Tarique Anwar, Jian Yang, Jia Wu:
dFDA-VeD: A Dynamic Future Demand Aware Vehicle Dispatching System. MobiQuitous 2020: 366-375 - [c66]Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan, Jilong Wang:
Graph Stochastic Neural Networks for Semi-supervised Learning. NeurIPS 2020 - [c65]Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao, Bin Wang:
Graph Geometry Interaction Learning. NeurIPS 2020 - 2019
- [c64]Xixun Lin, Hong Yang, Jia Wu, Chuan Zhou, Bin Wang:
Guiding Cross-lingual Entity Alignment via Adversarial Knowledge Embedding. ICDM 2019: 429-438 - [c63]Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Wenbin Hu, Qianli Xing:
DeepTrust: A Deep User Model of Homophily Effect for Trust Prediction. ICDM 2019: 618-627 - [c62]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Jian Yang:
Social Trust Network Embedding. ICDM 2019: 678-687 - [c61]Xindong Wu, Jia Wu, Xiaoyi Fu, Jiachen Li, Peng Zhou, Xu Jiang:
Automatic Knowledge Graph Construction: A Report on the 2019 ICDM/ICBK Contest. ICDM 2019: 1540-1545 - [c60]Qiannan Zhu, Xiaofei Zhou, Jia Wu, Jianlong Tan, Li Guo:
Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs. IJCAI 2019: 1943-1949 - [c59]Anfeng Cheng, Chuan Zhou, Hong Yang, Jia Wu, Lei Li, Jianlong Tan, Li Guo:
Deep Active Learning for Anchor User Prediction. IJCAI 2019: 2151-2157 - [c58]Zhenyu Qiu, Wenbin Hu, Jia Wu, Zhongzheng Tang, Xiaohua Jia:
Noise-Resilient Similarity Preserving Network Embedding for Social Networks. IJCAI 2019: 3282-3288 - [c57]Peiyao Li, Weiliang Zhao, Jian Yang, Jia Wu:
CoTrRank: Trust Evaluation of Users and Tweets. IJCAI 2019: 6542-6544 - [c56]Qi Huang, Chuan Zhou, Jia Wu, Mingwen Wang, Bin Wang:
Deep Structure Learning for Rumor Detection on Twitter. IJCNN 2019: 1-8 - [c55]Fanzhen Liu, Jia Wu, Chuan Zhou, Jian Yang:
Evolutionary Community Detection in Dynamic Social Networks. IJCNN 2019: 1-7 - [c54]Mengyu Zheng, Chuan Zhou, Jia Wu, Li Guo:
Smooth Deep Network Embedding. IJCNN 2019: 1-8 - [c53]Pinghua Xu, Wenbin Hu, Jia Wu, Bo Du:
Link Prediction with Signed Latent Factors in Signed Social Networks. KDD 2019: 1046-1054 - [c52]Qianli Xing, Weiliang Zhao, Jian Yang, Jia Wu, Qi Wang, Mei Wang:
GroExpert: A Novel Group-Aware Experts Identification Approach in Crowdsourcing. WISE 2019: 3-17 - [c51]Naime Ranjbar Kermany, Weiliang Zhao, Jian Yang, Jia Wu:
ReInCre: Enhancing Collaborative Filtering Recommendations by Incorporating User Rating Credibility. WISE Workshops 2019: 64-72 - 2018
- [c50]Chun-Yi Liu, Chuan Zhou, Jia Wu, Yue Hu, Li Guo:
Social Recommendation with an Essential Preference Space. AAAI 2018: 346-353 - [c49]Liangchen Song, Bo Du, Lefei Zhang, Liangpei Zhang, Jia Wu, Xuelong Li:
Nonlocal Patch Based t-SVD for Image Inpainting: Algorithm and Error Analysis. AAAI 2018: 2419-2426 - [c48]Haibo Wang, Chuan Zhou, Jia Wu, Weizhen Dang, Xingquan Zhu, Jilong Wang:
Deep Structure Learning for Fraud Detection. ICDM 2018: 567-576 - [c47]Jia Shao, Bo Du, Chen Wu, Jia Wu, Ruimin Hu, Xuelong Li:
VCF: Velocity Correlation Filter, Towards Space-Borne Satellite Video Tracking. ICME 2018: 1-6 - [c46]Pan Xiao, Bo Du, Jia Wu, Lefei Zhang, Ruimin Hu, Xuelong Li:
TLR: Transfer Latent Representation for Unsupervised Domain Adaptation. ICME 2018: 1-6 - [c45]Pan Xiao, Bo Du, Shuang Yun, Xue Li, Yipeng Zhang, Jia Wu:
Probabilistic Graph Embedding for Unsupervised Domain Adaptation. ICPR 2018: 1283-1288 - [c44]Min Fu, Chi Man Wong, Hai Zhu, Yanjun Huang, Yuanping Li, Xi Zheng, Jia Wu, Jian Yang, Chi-Man Vong:
DAliM: Machine Learning Based Intelligent Lucky Money Determination for Large-Scale E-Commerce Businesses. ICSOC 2018: 740-755 - [c43]Li Gao, Hong Yang, Chuan Zhou, Jia Wu, Shirui Pan, Yue Hu:
Active Discriminative Network Representation Learning. IJCAI 2018: 2142-2148 - [c42]Sihan Ma, Lefei Zhang, Wenbin Hu, Yipeng Zhang, Jia Wu, Xuelong Li:
Self-Representative Manifold Concept Factorization with Adaptive Neighbors for Clustering. IJCAI 2018: 2539-2545 - [c41]Li Gao, Hong Yang, Jia Wu, Chuan Zhou, Weixue Lu, Yue Hu:
Recommendation with Multi-Source Heterogeneous Information. IJCAI 2018: 3378-3384 - [c40]Feng Zhu, Yan Wang, Chaochao Chen, Guanfeng Liu, Mehmet A. Orgun, Jia Wu:
A Deep Framework for Cross-Domain and Cross-System Recommendations. IJCAI 2018: 3711-3717 - [c39]Yaoming Cai, Zhihua Cai, Meng Zeng, Xiaobo Liu, Jia Wu, Guangjun Wang:
A Novel Deep Learning Approach: Stacked Evolutionary Auto-encoder. IJCNN 2018: 1-8 - [c38]Lin Cui, Caiyin Wang, Jia Wu, Jian Yang, Michael Sheng:
Individual Interest and Trust Driving Collective Intelligence Awareness for Social Recommendation. IJCNN 2018: 1-6 - [c37]Mengyu Zheng, Chuan Zhou, Jia Wu, Shirui Pan, Jinqiao Shi, Li Guo:
FraudNE: a Joint Embedding Approach for Fraud Detection. IJCNN 2018: 1-8 - [c36]Qikui Zhu, Bo Du, Jia Wu, Pingkun Yan:
A Deep Learning Health Data Analysis Approach: Automatic 3D Prostate MR Segmentation with Densely-Connected Volumetric ConvNets. IJCNN 2018: 1-6 - [c35]Chenglong Dai, Jia Wu, Dechang Pi, Lin Cui:
Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification. SDM 2018: 558-566 - 2017
- [c34]Li Gao, Jia Wu, Chuan Zhou, Yue Hu:
Collaborative Dynamic Sparse Topic Regression with User Profile Evolution for Item Recommendation. AAAI 2017: 1316-1322 - [c33]Yongshan Zhang, Jia Wu, Zhihua Cai, Siwei Jiang:
Pre-trained Extreme Learning Machine. ICONIP (5) 2017: 14-23 - [c32]Chun-Yi Liu, Chuan Zhou, Jia Wu, Hongtao Xie, Yue Hu, Li Guo:
CPMF: A collective pairwise matrix factorization model for upcoming event recommendation. IJCNN 2017: 1532-1539 - [c31]Qinxue Meng, Jia Wu, John T. Ellis, Paul J. Kennedy:
Dynamic island model based on spectral clustering in genetic algorithm. IJCNN 2017: 1724-1731 - 2016
- [c30]Chuan Zhou, Weixue Lu, Peng Zhang, Jia Wu, Yue Hu, Li Guo:
On the Minimum Differentially Resolving Set Problem for Diffusion Source Inference in Networks. AAAI 2016: 79-86 - [c29]Jia Wu, Shirui Pan, Peng Zhang, Xingquan Zhu:
Direct Discriminative Bag Mapping for Multi-Instance Learning. AAAI 2016: 4274-4275 - [c28]Qinzhe Zhang, Jia Wu, Hong Yang, Weixue Lu, Guodong Long, Chengqi Zhang:
Global and Local Influence-based Social Recommendation. CIKM 2016: 1917-1920 - [c27]Li Gao, Jia Wu, Zhi Qiao, Chuan Zhou, Hong Yang, Yue Hu:
Collaborative Social Group Influence for Event Recommendation. CIKM 2016: 1941-1944 - [c26]Yongshan Zhang, Jia Wu, Chuan Zhou, Peng Zhang, Zhihua Cai:
Multiple-Instance Learning with Evolutionary Instance Selection. DASFAA (1) 2016: 229-241 - [c25]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 - [c24]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 - [c23]Li Gao, Jia Wu, Hong Yang, Zhi Qiao, Chuan Zhou, Yue Hu:
Semi-Data-Driven Network Coarsening. IJCAI 2016: 1483-1489 - [c22]Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Yang Wang:
Tri-Party Deep Network Representation. IJCAI 2016: 1895-1901 - [c21]Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu:
Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness. IJCAI 2016: 2167-2173 - [c20]Qin Zhang, Jia Wu, Hong Yang, Yingjie Tian, Chengqi Zhang:
Unsupervised Feature Learning from Time Series. IJCAI 2016: 2322-2328 - [c19]Yu Bai, Haishuai Wang, Jia Wu, Yun Zhang, Jing Jiang, Guodong Long:
Evolutionary lazy learning for Naive Bayes classification. IJCNN 2016: 3124-3129 - [c18]Haishuai Wang, Jia Wu, Chuan Zhou, Zhenyan Ji, Jun Wu:
Mining subcascade features for cascade outbreak prediction in big networks. IJCNN 2016: 3942-3949 - [c17]Shoujin Wang, Wei Liu, Jia Wu, Longbing Cao, Qinxue Meng, Paul J. Kennedy:
Training deep neural networks on imbalanced data sets. IJCNN 2016: 4368-4374 - [c16]Shan Xue, Jie Lu, Jia Wu, Guangquan Zhang, Li Xiong:
Multi-instance graphical transfer clustering for traffic data learning. IJCNN 2016: 4390-4395 - [c15]Weixue Lu, Chuan Zhou, Jia Wu, Chun-Yi Liu, Li Gao, Yue Hu:
A recursive method for big network influence estimation. IJCNN 2016: 4709-4714 - 2015
- [c14]Haishuai Wang, Peng Zhang, Jia Wu, Shirui Pan:
Mining Top-k Minimal Redundancy Frequent Patterns over Uncertain Databases. ICONIP (4) 2015: 111-119 - [c13]Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Multi-Graph-View Learning for Complicated Object Classification. IJCAI 2015: 3953-3959 - [c12]Yongshan Zhang, Zhihua Cai, Jia Wu, Xinxin Wang, Xiaobo Liu:
A memetic algorithm based extreme learning machine for classification. IJCNN 2015: 1-8 - 2014
- [c11]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 - [c10]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang:
Multi-graph-view Learning for Graph Classification. ICDM 2014: 590-599 - [c9]Jia Wu, Shirui Pan, Zhihua Cai, Xingquan Zhu, Chengqi Zhang:
Dual instance and attribute weighting for Naive Bayes classification. IJCNN 2014: 1675-1679 - [c8]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 - [c7]Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-Instance Learning from Positive and Unlabeled Bags. PAKDD (1) 2014: 237-248 - [c6]Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-Graph Learning with Positive and Unlabeled Bags. SDM 2014: 217-225 - 2013
- [c5]Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai:
Multi-instance Multi-graph Dual Embedding Learning. ICDM 2013: 827-836 - [c4]Jia Wu, Zhihua Cai, Xingquan Zhu:
Self-adaptive probability estimation for Naive Bayes classification. IJCNN 2013: 1-8 - [c3]Jia Wu, Zhihua Cai, Sanyou Zeng, Xingquan Zhu:
Artificial immune system for attribute weighted Naive Bayes classification. IJCNN 2013: 1-8 - 2009
- [c2]Jia Wu, Zhechao Gao, Chenxi Hu:
An Empirical Study on Several Classification Algorithms and Their Improvements. ISICA 2009: 276-286 - 2008
- [c1]Liangxiao Jiang, Chaoqun Li, Jia Wu, Jian Zhu:
A Combined Classification Algorithm Based on C4.5 and NB. ISICA 2008: 350-359
Editorship
- 2018
- [e1]Qingfeng Chen, Jia Wu, Shichao Zhang, Changan Yuan, Lynn Batten, Gang Li:
Applications and Techniques in Information Security - 9th International Conference, ATIS 2018, Nanning, China, November 9-11, 2018, Proceedings. Communications in Computer and Information Science 950, Springer 2018, ISBN 978-981-13-2906-7 [contents]
Informal and Other Publications
- 2023
- [i50]Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu C. Aggarwal, Hao Peng, Wenbin Hu, Edwin Hancock, Pietro Liò:
A Comprehensive Survey of Graph-level Learning. CoRR abs/2301.05860 (2023) - [i49]Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu:
Unbiased and Efficient Self-Supervised Incremental Contrastive Learning. CoRR abs/2301.12104 (2023) - [i48]Lingfeng Zhong, Jia Wu, Qian Li, Hao Peng, Xindong Wu:
A Comprehensive Survey on Automatic Knowledge Graph Construction. CoRR abs/2302.05019 (2023) - [i47]Nasrin Shabani, Jia Wu, Amin Beheshti, Jin Foo, Ambreen Hanif, Maryam Shahabikargar:
A Survey on Graph Neural Networks for Graph Summarization. CoRR abs/2302.06114 (2023) - [i46]Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, Hao Peng, Jianxin Li, Jia Wu, Ziwei Liu, Pengtao Xie, Caiming Xiong, Jian Pei, Philip S. Yu, Lichao Sun:
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT. CoRR abs/2302.09419 (2023) - [i45]Zitai Qiu, Jia Wu, Jian Yang, Xing Su, Charu C. Aggarwal:
Heterogeneous Social Event Detection via Hyperbolic Graph Representations. CoRR abs/2302.10362 (2023) - [i44]Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu:
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks. CoRR abs/2302.11396 (2023) - [i43]Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu:
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization. CoRR abs/2303.09778 (2023) - [i42]Xingcheng Fu, Yuecen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li:
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification. CoRR abs/2304.05059 (2023) - [i41]Fu Lin, Xuexiong Luo, Jia Wu, Jian Yang, Shan Xue, Zitong Wang, Haonan Gong:
Discriminative Graph-level Anomaly Detection via Dual-students-teacher Model. CoRR abs/2308.01947 (2023) - [i40]Xing Su, Jian Yang, Jia Wu, Zitai Qiu:
Hy-DeFake: Hypergraph Neural Networks for Detecting Fake News in Online Social Networks. CoRR abs/2309.02692 (2023) - [i39]Jiaqian Ren, Hao Peng, Lei Jiang, Zhiwei Liu, Jia Wu, Zhengtao Yu, Philip S. Yu:
Uncertainty-guided Boundary Learning for Imbalanced Social Event Detection. CoRR abs/2310.19247 (2023) - [i38]Chuang Liu, Wenhang Yu, Kuang Gao, Xueqi Ma, Yibing Zhan, Jia Wu, Bo Du, Wenbin Hu:
Careful Selection and Thoughtful Discarding: Graph Explicit Pooling Utilizing Discarded Nodes. CoRR abs/2311.12644 (2023) - [i37]Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu, Bo Du:
Exploring Sparsity in Graph Transformers. CoRR abs/2312.05479 (2023) - 2022
- [i36]Beihang Song, Jing Li, Shan Xue, Jun Chang, Jia Wu, Jun Wan, Tianpeng Liu:
Single-stage Rotate Object Detector via Two Points with Solar Corona Heatmap. CoRR abs/2202.06565 (2022) - [i35]Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng:
Curvature Graph Generative Adversarial Networks. CoRR abs/2203.01604 (2022) - [i34]Xusheng Zhao, Jia Wu, Hao Peng, Amin Beheshti, Jessica Monaghan, David McAlpine, Heivet Hernandez-Perez, Mark Dras, Qiong Dai, Yangyang Li, Philip S. Yu, Lifang He:
Deep Reinforcement Learning Guided Graph Neural Networks for Brain Network Analysis. CoRR abs/2203.10093 (2022) - [i33]Chuang Liu, Yibing Zhan, Chang Li, Bo Du, Jia Wu, Wenbin Hu, Tongliang Liu, Dacheng Tao:
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities. CoRR abs/2204.07321 (2022) - [i32]Taotao Cai, Quan Z. Sheng, Xiangyu Song, Jian Yang, Wei Emma Zhang, Jia Wu, Philip S. Yu:
A Survey on Location-Driven Influence Maximization. CoRR abs/2204.08005 (2022) - [i31]Yutong Qu, Wei Emma Zhang, Jian Yang, Lingfei Wu, Jia Wu, Xindong Wu:
Embedding Knowledge for Document Summarization: A Survey. CoRR abs/2204.11190 (2022) - [i30]Jiaqian Ren, Lei Jiang, Hao Peng, Zhiwei Liu, Jia Wu, Philip S. Yu:
Evidential Temporal-aware Graph-based Social Event Detection via Dempster-Shafer Theory. CoRR abs/2205.12179 (2022) - [i29]Ge Zhang, Jia Wu, Jian Yang, Shan Xue, Wenbin Hu, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu Aggarwal:
Graph-level Neural Networks: Current Progress and Future Directions. CoRR abs/2205.15555 (2022) - [i28]Ruitong Zhang, Hao Peng, Yingtong Dou, Jia Wu, Qingyun Sun, Jingyi Zhang, Philip S. Yu:
Automating DBSCAN via Deep Reinforcement Learning. CoRR abs/2208.04537 (2022) - [i27]Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He:
From Known to Unknown: Quality-aware Self-improving Graph Neural Network for Open Set Social Event Detection. CoRR abs/2208.06973 (2022) - [i26]Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu:
Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees. CoRR abs/2209.01539 (2022) - [i25]Yuecen Wei, Xingcheng Fu, Qingyun Sun, Hao Peng, Jia Wu, Jinyan Wang, Xianxian Li:
Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation. CoRR abs/2210.00538 (2022) - [i24]Fanzhen Liu, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu C. Aggarwal:
DAGAD: Data Augmentation for Graph Anomaly Detection. CoRR abs/2210.09766 (2022) - [i23]Fengzhao Shi, Ren Li, Yanan Cao, Yanmin Shang, Lanxue Zhang, Chuan Zhou, Jia Wu, Shirui Pan:
VR-GNN: Variational Relation Vector Graph Neural Network for Modeling both Homophily and Heterophily. CoRR abs/2211.14523 (2022) - [i22]Xing Su, Jian Yang, Jia Wu, Yuchen Zhang:
Mining User-aware Multi-relations for Fake News Detection in Large Scale Online Social Networks. CoRR abs/2212.10778 (2022) - 2021
- [i21]Qingyun Sun, Hao Peng, Jianxin Li, Jia Wu, Yuanxing Ning, Philip S. Yu, Lifang He:
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. CoRR abs/2101.08170 (2021) - [i20]Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, Philip S. Yu:
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs. CoRR abs/2101.08747 (2021) - [i19]Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan, Yanan Cao, Bin Wang:
Task-adaptive Neural Process for User Cold-Start Recommendation. CoRR abs/2103.06137 (2021) - [i18]Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu:
A Comprehensive Survey on Community Detection with Deep Learning. CoRR abs/2105.12584 (2021) - [i17]Yang Guo, Tarique Anwar, Jian Yang, Jia Wu:
dFDA-VeD: A Dynamic Future Demand Aware Vehicle Dispatching System. CoRR abs/2106.05737 (2021) - [i16]Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Quan Z. Sheng, Hui Xiong:
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning. CoRR abs/2106.07178 (2021) - [i15]Xingcheng Fu, Jianxin Li, Jia Wu, Qingyun Sun, Cheng Ji, Senzhang Wang, Jiajun Tan, Hao Peng, Philip S. Yu:
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network. CoRR abs/2110.07888 (2021) - [i14]Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu:
Graph Structure Learning with Variational Information Bottleneck. CoRR abs/2112.08903 (2021) - 2020
- [i13]Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Jian Yang, Philip S. Yu:
Deep Learning for Community Detection: Progress, Challenges and Opportunities. CoRR abs/2005.08225 (2020) - [i12]Qi Huang, Junshuai Yu, Jia Wu, Bin Wang:
Heterogeneous Graph Attention Networks for Early Detection of Rumors on Twitter. CoRR abs/2006.05866 (2020) - [i11]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu:
Opinion Maximization in Social Trust Networks. CoRR abs/2006.10961 (2020) - [i10]Feng Zhu, Yan Wang, Chaochao Chen, Guanfeng Liu, Mehmet A. Orgun, Jia Wu:
A Deep Framework for Cross-Domain and Cross-System Recommendations. CoRR abs/2009.06215 (2020) - [i9]Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao, Bin Wang:
Graph Geometry Interaction Learning. CoRR abs/2010.12135 (2020) - [i8]Chaochao Chen, Jamie Cui, Guanfeng Liu, Jia Wu, Li Wang:
Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications. CoRR abs/2011.10180 (2020) - 2019
- [i7]Anfeng Cheng, Chuan Zhou, Hong Yang, Jia Wu, Lei Li, Jianlong Tan, Li Guo:
Deep Active Learning for Anchor User Prediction. CoRR abs/1906.07318 (2019) - 2018
- [i6]Qinxue Meng, Jia Wu, John Ellisy, Paul J. Kennedy:
Dynamic Island Model based on Spectral Clustering in Genetic Algorithm. CoRR abs/1801.01620 (2018) - [i5]Chenglong Dai, Jia Wu, Dechang Pi, Lin Cui:
Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification. CoRR abs/1801.04510 (2018) - [i4]Pan Xiao, Bo Du, Jia Wu, Lefei Zhang, Ruimin Hu, Xuelong Li:
TLR: Transfer Latent Representation for Unsupervised Domain Adaptation. CoRR abs/1808.06206 (2018) - 2017
- [i3]Chengjun Li, Jia Wu:
Subpopulation Diversity Based Selecting Migration Moment in Distributed Evolutionary Algorithms. CoRR abs/1701.01271 (2017) - 2016
- [i2]Haishuai Wang, Jia Wu, Xingquan Zhu, Chengqi Zhang:
Time-Variant Graph Classification. CoRR abs/1609.04350 (2016) - [i1]Dongkuan Xu, Jia Wu, Wei Zhang, Yingjie Tian:
PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning. CoRR abs/1612.03550 (2016)
Coauthor Index
[j137] [j135] [j131] [j124] [j123] [j115] [j109] [j100] [j99] [j91] [j83] [j81] [c111] [c110] [c108] [c107] [c105] [c104] [c103] [c102] [c101] [c100] [c99] [c97] [c95] [c91] [c88] [c87] [c81] [c80] [i50] [i49] [i48] [i46] [i43] [i42] [i39] [i35] [i34] [i30] [i29] [i28] [i27] [i26] [i25] [i24] [i21] [i20] [i15] [i14]
[j138] [j129] [j127] [j112] [j97] [j95] [j94] [j91] [j86] [j73] [j72] [j71] [j70] [j64] [j63] [j62] [j50] [j49] [j40] [c127] [c126] [c125] [c124] [c115] [c114] [c113] [c112] [c111] [c101] [c98] [c95] [c94] [c93] [c85] [c84] [c83] [c79] [c78] [c75] [c72] [c70] [c67] [c63] [c62] [c57] [c55] [c52] [c51] [c44] [c38] [i50] [i45] [i41] [i40] [i32] [i31] [i29] [i24] [i22] [i18] [i17] [i16] [i13]
[j135] [j131] [j129] [j124] [j115] [j103] [j102] [j101] [j100] [j94] [j91] [j83] [j81] [j64] [j54] [j44] [j40] [j34] [j15] [j6] [c110] [c107] [c105] [c104] [c103] [c102] [c97] [c88] [c87] [c81] [c80] [c70] [c25] [i49] [i46] [i43] [i39] [i34] [i32] [i30] [i28] [i27] [i26] [i21] [i20] [i18] [i15] [i14] [i13]
[j132] [j129] [j121] [j114] [j97] [j95] [j72] [j50] [j40] [j36] [j25] [j18] [c122] [c109] [c101] [c95] [c92] [c86] [c85] [c82] [c75] [c74] [c73] [c70] [c66] [c65] [c64] [c59] [c56] [c55] [c54] [c50] [c48] [c43] [c41] [c37] [c34] [c32] [c30] [c27] [c26] [c23] [c18] [c15] [i50] [i29] [i24] [i23] [i19] [i18] [i13] [i9] [i7]
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