2024年12月10日 (二) 09:25的版本

研究成果

Selected Paper

2025

1. Baoming Zhang, MingCai Chen, Jianqing Song, Shuangjie Li, Jie Zhang, Chongjun Wang. Normalize then Propagate: Efficient Homophilous Regularization for Few-shot Semi-Supervised Node Classification. In Proceedings of AAAI 2025, Accepted
2. MingCai Chen, Yuntao Du., Wenyu Jiang, Baoming Zhang, Shuai Feng, Yi Xin, Chongjun Wang. Robust Logit Adjustment for Learning with Long-Tailed Noisy Data. In Proceedings of AAAI 2025, Accepted

2024

1. Song J., etc. Similarity-Navigated Conformal Prediction for Graph Neural Networks. In Proceedings of NIPS 2024, Accepted
2. Feng S., Wang C. When an Extra Rejection Class Meets Out-of-Distribution Detection in Long-tailed Image Classification Learning Systems. Neural Networks, 2024，178: 106485
3. He Q, .Jin C., Xia Y., Wang C. and Wang C.  Some Can Be Better Than All: Multimodals Star Transformer for Visual Dialog. In Proceedings of IEEE ICIP 2024, Accepted
4. Zhang J., etc.  Shapley-Optimized Reinforcement Learning for Human-Machine Collaboration Policy. In Proceedings of DASFAA 2024, Accepted
5. Guo M., etc. SMILE: Spiking Multi-modal Interactive Label-guided Enhancement Network for Emotion Recognition. In Proceedings of ICME 2024, Accepted
6. Yuntao Du, Siqi Luo, yi Xin, MingCai Chen, Shuai Feng, Mujie Zhang, Chongjun Wang. Multi-source Fully Test-Time Adaptation. In Proceedings of ICLR 2024 Workshop PML4LRs, Accepted
7. Liu Z., Xia C., He W., Wang C. Trustworthiness and Self-awareness in Large Language Models: An Exploration through the Think-Solve-Verify Framework. In Proceedings of Coling 2024: 16855-16866
8. Liu Z., Qian S., Xia C., Wang C. Are Transformer-based Models More Robust than CNN-based Models?. Neural Networks,  2024，172: 106091
9. Li S., etc. SEEKING SIMILARITIES WHILE REMOVING DIFFERENCES: GRAPH NEURAL NETWORKS BASED ON NODE CORRELATION. In Proceedings of ICASSP 2024, Accepted
10. Liu Z., etc. Understanding Data Augmentation from a Robustness Perspective. In Proceedings of ICASSP 2024, Accepted
11. Liu Z., etc. From Game Theory to Visual Recognition: Advancing DNN Robustness. In Proceedings of ICASSP 2024, Accepted
12. Jiang W., etc. EDOS: Diverse Outlier Sampling for Out-of-Distribution Detection. In Proceedings of ICLR 2024, Accepted
13. Liu M., Kirill K., Wang C. The Implementations and Applications of Elliptic Curve Cryptography. In Proceedings of CATA 2024( 39th International Conference on Computers and Their Applications), Best Paper Award.
14. Feng S., Jin P., Wang C. CASE: Exploiting Intra-class Compactness and Inter-class Separability of Feature Embeddings for Out-of-Distribution Detection. In Proceedings of AAAI 2024: 21081-21089
15.  Shanli Tan, Hao Cheng, Xiaohu Wu, Han Yu, Tiantian He, Yew Soon Ong, Chongjun Wang, Xiaofeng Tao. FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants. In Proceedings of AAAI 2024: 15231-15239
16. Yuntao Du, Haiyang Yang, Mingcai Chen, Hongtao Luo, Juan Jiang, Chongjun Wang. Generation, Augmentation, and Alignment: A Pseudo-Source Domain Based Method for Source-Free Domain Adaptation. Mach. Learn. 2024,113(6): 3611-3631
17. 吴骏等.一种基于算法机制设计的社会法则合成方法.软件学报, 2024, 35(3): 1440-1465

2023

1. Cao M.,Chen M., Song J., Fang C., Wang C. A Flexible Debiasing Framework for Fair Heterogeneous Information Network Embedding. In Proceedings of ECAI 2023,  2023, 343-350
2. Du Y., Jiang J., Luo H., Haiyang Yang , Mingcai Chen, and Chongjun Wang. Bidirectional View based Consistency Regularization for Semi-Supervised Domain Adaptation[J]. Transactions on Machine Learning Research, 2023:1-17
3. Cao M., Yuan J., Yu H., Zhang B. and Wang C. Self-supervised short text classification with heterogeneous graph neural networks.Expert Systems. 2023, 40(6):
4. Cheng H. etc.Exploring Leximin Principle for Fair Core-Selecting Combinatorial Auctions: Payment Rule Design and Implementation.  In Proceedings of IJCAI 2023, 2023, 2581-2588
5. Ma C., Chen Y., Guo P., Guo J., Wang C., Guo Y. Symmetric Shape-Preserving Autoencoder for Unsupervised Real Scene Point Cloud Completion. In Proceedings of CVPR 2023, 2023:13560-13569
6. Yuan J., Yu H., Cao M., Song J., Xie J., Wang C. Self-Supervised Robust Graph Neural Networks against Noisy Graphs and Noisy Labels[J]. Applied Intelligence, 2023: 53(21): 25154-25170
7. Shuai Feng, Wenyu Jiang, Mingcai Chen, Yuntao Du, Hao Cheng, Chongjun Wang.CESED: Exploiting Hyperspherical Predefined Evenly-Distributed Class Centroids for OOD Detection.  In Proceedings of SDM 2023:262-270
8. Wenyu Jiang, Yuxin Ge, Hao Cheng, Mingcai Chen, Shuai Feng, Chongjun Wang. READ: Aggregating Reconstruction Error into Out-of-distribution Detection.  In Proceedings of AAAI 2023, 2023: 14910-14918
9. Mingcai Chen, Hao Cheng, Yuntao Du, Ming Xu, Wenyu Jiang, Chongjun Wang. Two Wrongs Don’t Make a Right: Combating Confirmation Bias in Learning with Label Noise. In Proceedings of AAAI 2023, 2023:14765-14773
10. Shuwei Qian, Chongjun Wang. COM: Contrastive Masked-attention model for incomplete multimodal learning. Neural Networks. 2023: 162: 443-455
11. Cao M., Song J., Yuan J., Zhang B. and Wang C. Title: FairHELP: Fairness-Aware Heterogeneous Information Network Embedding for Link Prediction. In Proceedings of DASFAA 2023, 320-330
12. Xin Y., Luo S., Jin P., Du Y. and Wang C. Self-Training with Label-Feature-Consistency for Domain Adaptation. In Proceedings of DASFAA 2023, 84-89

2022

1. Zhang B. Xu M. Chen M., Chen M. Wang C. CopGAT: Co-propagation Self-supervised Graph Attention Network. In Proceedings of ISPA 2022: 18-25
2. Yu H., etc. DIPool: Degree-Induced Pooling for Hierarchical Graph Representation Learning. In Proceedings of ISPA 2022: 220-227
3. Changfeng Ma, Yang Yang, Jie Guo, Fei Pan, Chongjun Wang, Yanwen Guo. Unsupervised Point Cloud Completion and Segmentation by Generative Adversarial Autoencoding Network[C]. In Proceedings of  NIPS 2022
4. Zhendong Liu, Wenyu Jiang, Yi Zhang, Chongjun Wang. FIXC: A Method for Data Distribution Shifts Calibration via Feature Importance[C].  In Proceedings of ICTAI 2022: 153-160
5. Yuxin Ge, Hongtao Luo, Chen-Xuan Fang, Zhi-Wei Zhu, Chongjun Wan. MRM: Site Selection via Mutil-round Meanshift for Global Fairness[C].  In Proceedings of ICTAI 2022: 1245-1250
6. Yu H., Yuan J., Yao Y., and Wang C. Not All Edges are Peers: Accurate Structure-Aware Graph Pooling Networks[J]. Neural Networks, 2022, 156: 58-66
7. Xu M., Zhang B., Cao M., Yu H., Wang C. LSEGNN: Encode Local Topology Structure in Graph Neural Networks[C]. In Proceedings of IPCCC 2022: 49-56
8. Zhang Y., Shen J., Yu C., Wang C. Views Meet Labels: Personalized Relation Refinement Network for Multiview Multilabel Learning[J].IEEE Multim. 2022, 29(2): 104-113
9. Wu J., Cao J., Sun H., and Wang C. A Bayesian Optimal Social Law Synthesizing Mechanism for Strategic Agents[J]. JAAMAS, 2022, 36(2)
10. Du Y., Luo H., Yang H.,  Jiang J. and etc. InCo: Intermediate Prototype Contrast for Unsupervised Domain Adaptation[C]. In Proceedings of  ECML PKDD 2022: 642-658
11. Ming Xu, Baoming Zhang, Jinliang Yuan, Meng Cao, Chongjun Wang. NED-GNN: Detecting and Dropping Noisy Edges in Graph Neural Networks[C]. In Proceedings of  APWeb-WAIM 2022: 91-105
12. Xu M. etc. NC-GNN: Consistent Neighbors of Nodes Help More in Graph Neural Networks[J].Wireless Communications and Mobile Computing, Accepted
13. Lu H., Yang J., Fang W., Song X. and Wang C. A DNNs-based fusion model for COVID-19 rumor detection from online social media[J]. Data Technologies and Applications, 2022, 56(5): 806-824
14. Cui F., Chen Y., Du Y., Cao Y. and Wang C. Joint Feature and Labeling Function Adaptation for Unsupervised Domain Adaptation[C]. In Proceedings of  PAKDD2022, 432-446
15. Zhang Y. Zhu Y., Zhang Z., Wang C. Collaboration based Multi-modal Multi-label Learning[J]. Applied Intelligence, 2022, 52(12): 14204-14217
16. Zhang Y. Chen M. Shen J. Wang C. Tailor Versatile Multi-modal Learning for Multi-label Emotion Recognition. In Proceedings of  AAAI2022, 9100-9108
17. Chen M. Du Y., Zhang Y., Qian S. Wang C. Semi-Supervised Learning with Multi-Head Co-Training. In Proceedings of  AAAI2022, 6278- 6286
18. Jinliang Yuan, Yirong Yao,  Ming Xu, Hualei Yu, Junyuan Xie and Chongjun Wang.Graph Structure Learning based on Feature[J].IDA Journal, 2022, 26(6): 1539-1555
19. Jinliang Yuan, Meng Cao, Hao Chen, Hualei Yu, Junyuan Xie and Chongjun Wang.A Unified Structure Learning Framework for Graph Attention Networks.[J] NearalComputing, 2022, 495: 194-204
20. Zhang Y., Zhang Z., Chen M., Lu H., Zhang L., Wang C. LAMB: A Novel Algorithm of Label Collaboration based Multi-Label Learning. IDA Journal, 2022, 26(5): 1229-1245
21. Du Y., Zhang R., Zhang X., Yao Y., Lu H., Wang C. Learning transferable and discriminative features for unsupervised domain adaptation. IDA Journal, 2022, 26(2): 407-425.

2021

1. Huang Z., Zhang L., Zhang Y. Qian S. and Wang C. ransformer based Multi-output Regression Learning for Wastewater Treatment. In Proceedings of  ICTAI 2021, 608-703
2. Xiaowen Zhang, Yuntao Du, Rongbiao Xie and Chongjun Wang.Adversarial Separation Network for Cross-Network Node Classification. In Proceedings of  CIKM2021, 2618-2626
3. Yuntao Du, Jindong Wang, Wenjie Feng, Sinno Pan, Tao Qin, Renjun Xu, Chongjjun Wang. AdaRNN: Adaptive Learning and Forecasting of Time Series In Proceedings of  CIKM2021, 402-411
4. Jinliang Yuan, Hualei Yu, Meng Cao, Ming Xu, Junyuan Xie and Chongjun Wang.Semi-Supervised and Self-Supervised Classification with Multi-View Graph Neural Networks. In Proceedings of  CIKM2021, 2466-2476
5. Zhang J., Zhang B., Li K., Xu M. and Wang C. Parallel Counterfactual Regret Minimization in Crowdsourcing Imperfect-information Expanded Game. In Proceedings of  ISPA 2021, 1444-1451
6. Zhang J., Li K., Zhang B., Xu M. and Wang C. QMIMC: Q-Learning Model Based on Imperfect-information under Multi-agent Crowdtesting. In Proceedings of  ISPA 2021, 1110-1117
7. Xu M., Zhang L., Zhang B., Cao M., Yuan J. and Wang C. EPINE: Enhanced Proximity Information Network Embedding. In Proceedings of  ISPA 2021, 143-150
8. Cao M., Yuan J., Xu M., Yu H. and Wang C. Local Structural Aware Heterogeneous Information Network Embedding Based on Relational Self-Attention Graph Neural Networ. IEEE ACCESS, 2021, 9: 88301-88312
9. He Q., Qiao Y., Yang S.  and etc.Equitable Valuation of Crowdsensing for Machine Learning via Game Theory. In Proceedings of  WASA 2021, 133-141
10. He Q., Qiao Y., Yang S.  and etc. Robust and Efficient Mechanism Design for Heterogeneous Task Crowdsensing. In Proceedings of  WASA 2021, 99-107
11. Qiu C., Yao Y., and Du Y. Nested Dense Attention Network For Single Image Super-Resolution. In Proceedings of  ICMR2021, 250-258
12. Chen H.  and etc. False-name-proof mechanism for  time window coverage tasks in mobile crowdsensing. In Proceedings of  ICCCN 2021, 1-10
13. Yu Hualei, Yuan Jinliang, Cheng Hao, Cao Meng and Wang Chongjun. GSAPool: Gated Structure Aware Pooling for Graph Representation Learning. In Proceedings of  IJCNN 2021, 1-8
14. Zhang Y., and etc. Label-specific Alignment with Adversarial Multi-view Representation. In Proceedings of  ICME 2021
15. Yu H., Luo C., Du Y., Cheng H., Cao M. and Wang C. Dual Multi-Scale Pooling for Graph Representation Learning. In Proceedings of  DASFAA 2021: 375-384
16. Du Y.,  Cao Y., Zhou Y., Chen Y., Zhang R. and Wang C. Self Separation and Misseparation Impact Minimization for Open-Set Domain Adaptation. In Proceedings of  DASFAA 2021: 400-409
17. Du Y., Tan Z., Zhang X., Yao Y., Yu H. and Wang C. Unsupervised domain adaptation with unified joint distribution alignment regular. In Proceedings of  DASFAA 2021: 449-464
18. Du Y., Chen Y., Cui F., Zhang X. and Wang C. Cross-domain error minimization for unsupervised domain adaptation regular. In Proceedings of  DASFAA 2021: 429-448
19. Zhang Y., Shen J., Yu C. and Wang C.. Relation-aware Alignment Attention Network for Multi-view Multi-label Learning regular. In Proceedings of  DASFAA 2021: 465-482
20. Zhang Y., Shen J., Zhang Z. and Wang C. Partial Modal Conditioned Gans for Multi-modal Multi-label Learning with Arbitrary Modal-missing Regular. In Proceedings of  DASFAA 2021: 413-428

2020

1. Shen J., Zhang Y., Yu C., Wang C. Multi-view Multi-label Learning with Dual-Attention Networks for Stroke Screen. In Proceedings of  BIBM 2020, 1124-1128
2. Pang B., Bao H., Wang C. Feature-Aware Attentive Variational Auto-Encoder for Top-N Recommendation.  In Proceedings of  ICTAI 2020, 53-58
3. Qiao Y., Wu J., Cheng H., Huang Z., Wang C. Truthful Mechanisms Design for Multi-region Mobile Crowdsensing[J]. Wireless Communications and Mobile Computing. 2020 (8834983) :1-15
4. Chen Q, Du Y, Tan Z, Zhang Y  and Wang C. Unsupervised Domain Adaptation with Joint Domain-Adversarial Reconnstructionn Networks[C]. In Proceedings of  ECML - PKDD 2020, 640-656
5. Zhang Y,, Zhang Z., Zhu Y., Zhang L., and Wang C. Discriminative Multi-label Moel Reuse for Multi-label Learning[C]. In Proceedings of  APWeb - WAIM 2020, 725-739
6. Cao M., Ma Q., Zhu K., Xu M., Wang C..Heterogeneous Information Network Embedding with Convolutional Graph Attention Networks[C]. In Proceedings of  IJCNN 2020, 1-8
7. Zhang Y., Shen J., Zhang Z., Zhang L., Wang C.. Rethinking Modal-oriented Label Correlations for Multi-modal Multi-label Learning[C]. In Proceedings of  IJCNN 2020, 1-8
8. Wu J , Zhang L , Wang C  and etc.  A Multi-unit Profit Competitive Mechanism for Cellular Traffic Offloading[C]. In Proceedings of  AAAI2020, 2020: 2294-2301
9. Cheng H., Zhang W., Zhang Y.,  Zhang L. and Wanng C.. Fast core pricing algorithm for path auctions[J]. JAAMAS, 2020, 34(1)
10. Du Y. Tan Z. Chen Q. Zhang Y. Wang C. Homogeneous Online Transfer Learning with Online Distribution Discrepancy Minimization[C], In Proceedings of ECAI2020, 1111-1118
11. Zhang Y. Shen J. Zhang Z. Wang C.  Common and Discriminative Semantic Pursuit for Multi-modal Multi-label learning[C], In Proceedings of ECAI2020, 1666-1673

2019 

1. Zhang Y., Zhang Z., Cheng H., Lu H., Zhang L., Wang C., Xie J.. Win-win Cooperation: A Novel Dual-Modal Dual-Label Algorithm for Membrane Proteins Function Pre-screen[C]. In Proceedings of BIBM 2019, San Diego, California, USA, Nov18-21, 2019: 102-106
2. Zhang L., Ma X., Shi P.Bi S and Wang C.RegCNN: A Deep Multi-output Regression Method for Wastewater Treatment[C]. In Proceedings of ICTAI 2019. November 4-6 2019, Portland, Oregon
3. Liu F., Lei C., Liu H., Wang C. A Probabilistic Forward Search Value Iteration Algorithm for POMDP[C]. In Proceedings of ICTAI 2019. November 4-6 2019, Portland, Oregon
4. Pan Y., Gan J., Ran X., Wang C. Multi-Granularity Position-Aware Convolutional Memory Network for Aspect-Based Sentiment Analysis[C]. In Proceedings of ICTAI 2019. November 4-6 2019, Portland, Oregon
5. Zhu K, Cao M, Lu H. MALP: A More Effective Meta-Paths Based Link Prediction Method in Partially Aligned Heterogeneous Social Networks[C]. In Proceedings of ICTAI 2019. November 4-6 2019, Portland, Oregon
6. Cao M., Ma X., Wang C.. Heterogeneous Information Network Embedding with Meta-path Based Graph Attention Networks[C]. In Proceedings of ICANN 2019: 622-634
7. Luo X., Ran X., Sun W., Xu Y., Wang C.. A Label-Specific Attention-Based Network with Regularized Loss for Multi-label Classification[C]. In Proceedings of ICANN 2019: 731-742
8. Gao Y., Wang C.. Symmetrical Adversarial Training Nets: A Novel Model for Text Generation[C]. In Proceedings of ICANN 2019: 269-280
9. Ran X., Pan Y., Sun W. and Wang C.. Learn to Select via Hierarchical Gate Mechanism for Aspect-Based Sentiment Analysis[C]. In Proceedings of IJCAL 2019: 5160-5167
10. Qiao Y., Wu J., Zhang L. and Wang C..Mechanism Design for Cross-Market Task Crowdsourcing[C]. In 2019 IEEE/ACM International Symposium On Quality of Service(IWQoS), 9:1-9:9
11. Zhan Q., Zhuo, W., Hu W., Emeryx S., Wang C. and Liu Y..Opinion Mining in Online Media for Public Health Campaigns[J]. Journal of Medical Imaging and Health Informatics, 2019,9(7): 1448-1452
12. Zhang Y., Wang C. and etc..Many Can Be Better Than All: A Novel Instance-oriented algorithm for Multi-modal Multi-lable Problem[C]. In Proceedings of ICME 2019, 838-843
13. Sun W., Ran X.. Luo X., and Wang C..An Efficient Framework by Topic Model for Multi-label Text Classification[C]. In Proceedings of IJCNN 2019, 1-7
14. Xu Y., Ran X.. Sun W., Luo X. and Wang C..Gated Neural Network with Regularized Loss for Multi-label Text Classification[C]. In Proceedings of IJCNN 2019, 1-8
15. Zeng C., Zhang Y.. Lu H. and Wang C..GADGET: Using Gated GRU for Biomedical Event Trigger Detection[C]. In Proceedings of IJCNN 2019, 1-8
16. Wu J., Zhang Y., Qiao Y., Zhang L., Wang C., Xie J.Multi-unit Budget Feasible Mechanisms for Cellular Traffic Offloading[C]. In Proceedings of AAMAS 2019, 1693-1701
17. Lu Q., Xu Y, Yang R., Li N., and Wang C.. Serial and Parallel Recurrent Convolutional Neural Networks for Biomedical Named Entity Recoginiton[C]. In Proceedings of DASFAA 2019, Chiang Mai, Thailand, Apr. 22-25, 2019: 439-443
18. Ran X., Pan Y., Sun W. and Wang C.. Modeling More Globally: A Hierarchical Attention Network via Multi-Task Learning for Aspect-Based Sentiment Analysis[C]. In Proceedings of DASFAA 2019, Chiang Mai, Thailand, Apr. 22-25, 2019: 505-509 
19. Peng Y, Huang E., Chen G., Wang C and Xie J. A General Framework for Multi-Label Learning Towards Class Correlations and Class Imbalance[J]. Intelligent Data Analysis, 2019, 23(2): 371-383
20. Lu H., Kang N., Li Y., Zhan Q., Xie J., and Wang C. Utilizing Recurrent Neural Network for Topic Discovery in Short Text Scenarios[J]. Intelligent Data Analysis, 2019, 23(2): 259-277
21. YangJ, Yang R., Lu H., Wang C., Xie J. Multi-Entity Aspect-Based Sentiment Analysis with Context, Entity, Aspect Memory and Dependency Information[J]. ACM Transactions on Asian and Low-resource Language Information Processing, 2019, 47: 1-22
22. Pang B., Wang C. A Novel Top-N Recommendation Approach Based on Conditional Variational Auto-Encoder[C]. In Proceedings of PAKDD2019, Macau, China. Apr.14-17, 2019: 357-368

2018

1. Lu H, Li Y, Tang C, Wang C and Xie J. Constructing Pseudo Documents with Semantic Siliarity for Short Text Topic Descovery. In Proceedings of ICONIP 2018,  SiemReap, Cambodia. Dec.13-16,2018:437-449
2. QiaoY, SONG Y, WANG N, and etc, A False-name-proof Protocol for Multicast Routing Auctions. In Proceedings of ISPA2018, Melbourne, Australia, Dec. 11-13, 2018: 72-79.
3. QiaoY, GU Y, Wu J and etc, A Truthful Profit-oriented Mechanism for Mobile Crowdsensing. In Proceedings of ISPA2018, Melbourne, Australia, Dec. 11-13, 2018:64-71.
4. Feng Y., Tang J., Wang C., XieJ. CuAPSS: A Hybrid CUDA Solution for AllPairsSimilarity Search. In Proceedings of ICA3PP 2018. Guangzhou, China Nov. 15-17, 2018: 421–436
5. Lu H., Ge G., Li Y., Wang C., Xie J. Exploiting Global Semantic Similarity Biterms for Short-text Topic Discovery.In Proceedings of ICTAI 2018. Volos, Greece: 975-982
6. Chen Q., Du Y, Xu M., Wang C. HetEOTL: An Algorithm for Heterogeneous Online Transfer Learning.In P'roceedings of ICTAI 2018..Volos, Greece: 350-357
7. Du Y.. Chen Q., Lu H., Wang C. Online Single Homogeneous Source Transfer Learning Based on AdaBoos.In Proceedings of ICTAI 2018. Volos, Greece:344-349
8. Feng Y., Tang J., Liu M., Wang C., Xie J. Fast Document Cosine Similarity Self-Join on GPUs. In Proceedings of ICTAI 2018. Volos, Greece:205-212
9. Chen G, Peng Y, Wang C and etc. Multi- Label Classification via Label -Toci Pairs. In Proceedings of APWEB\WAIM-18, Macao. Jul.23-25, 2018:32-44
10. Cheng H, Zhang L, Wu J and Wang C, Optimal Constraint Coolection for Core-Selecting Path Mechanism. In Proceedings of AAMAS 2018,2018:41-49.
11. Zhan Q., Emery S., Yu, P., Wang C., Liu Y. Different Anti-Vaping Campaigns Attracting the Same Opponent Community. IEEE TRANSACTIONS ON NANOBIOSCIENCE. 2018, 17(4): 409-416
12. Yang J, Yang R and Xie J. Multi-Entity Aspect-Based Sentiment Analysis with Context, Entity and Aspect Memory. In Proceedings of AAAI 2018. New Oleans, Louisiana. USA.2018:6029-6036
13. 王崇骏，史忠植，常量，王文剑. 多智能体系统及应用.北京：清华大学出版社, ISBN: 978-7- 302- 48777-7.

2017

1. Zhan Q, Tan L, Sherry E, Philip Y, Wang C. Community Detection on Anti-vaping Campaign Audience. In Proceedings of BIBM-17. Kansan City, MO. USA.:891-894
2. Peng Y, Tang C, Chen G, Xie J, Wang C. Multi-Label Learning by Exploiting label Correlations for TCM Diagnosing Parkinson's Disease. In Proceedings of BIBM-17. Kansan City, MO. USA.:590-594
3. Peng Y, Chen G, Zhai C, Wang C, Xie J. Multi-Label Learning by Exploiting label Correlations with LDA. In Proceedings of ICTAI-17. Boston, MA. USA.:168-174
4. Xie L, Wang L, Lu H, Li N, Wang C. Topics may Evolve: Using Complaint Date for Analysis. In Proceedings of ICTAI-17. Boston, MA. USA.:1296-1303
5. 王崇骏. 大数据价值期望探讨. 大数据.  2017,4：91-103【约稿】
6. Liu L, Zhang Y, Liu M, Wang C, Wang J. A-MapCG: An Adaptive MapReduce Framework for GPUs. In Proceedings of NAS-17. Shen Zhen, China, 2017.:1-8
7. Qiao Y, Wu J, Zhang L, Wang C. Viral Marketing for Digital Goods in Social Networks[C]. In Proceedings of APWEB\WAIM-17. Beijing, China, 2017.:377-390
8. Xu M, Cai Y, Wu H, Wang C, Li N. Intensity of Relationship between Words: Using Word Triangles in Topic Discovery for Short Texts. In Proceedings of APWEB\WAIM-17. Beijing, China, 2017.:642-649
9. Wang N, Wu J, Wang C, Zhang L. Approximation for Strategic Single Point Weighted Steiner Tree Problem[C]. In Proceedings of ICA-17. Beijing, China, 2017.
10. Wu J, Zhang L, Wang C, Xie J. Mechanism Design for Social Law Synthesis under Incomplete Information[C]. In Proceedings of AAMAS-17. São Paulo, Brazil, 2017: 1757-1759.
11. Wu J, Zhang L, Wang C, Xie J. Synthesizing Optimal Social Laws for Strategical Agents via Bayesian Mechanism Design[C]. In Proceedings of AAMAS-17. São Paulo, Brazil, 2017: 1214-1222.
12. Lu H, Xie L, Kang N, Wang C and Xie J. Don't Forget the Quantifiable Relationship between Words: Using Recurrent Neural Network for Short Text Topic Discovery[C]. In Proceedings of AAAI-17. San Francisco, USA, 2017: 1192-1198.
13. Jiang J, Shi P, An B, Yu J, Wang C. Measuring the social influences of scientist groups based on multiple types of collaboration relations[J].Information Processing and Management, 2017, 53(1): 1-20.

2016

1. 王崇骏.大数据思维与应用攻略.北京：机械工业出版社, ISBN: 978-7- 111- 54261- 2.
2. Li Y, Li H, Wang Q, Wang C and Fan X. Traditional Chinese Medicine Formula Evaluation Using Multi-instance Multi-label Framework[C]. In Proceedings of BIBM-16. Shenzhen, China, 2016: 484-488.
3. Zhan Q, Zhang J, Yu P, Emery S and Xie J. Inferring Social Influence of Anti-Tobacco Mass Media Campaigns[C]. In Proceedings of BIBM-16. Shenzhen, China, 2016: 805-812.
4. Liu L, Liu M, Wang C, Wang J. Compile-time Automatic Synchronization Insertion and Redundant Synchronization Elimination for GPU Kernels[C]. In Proceedings of ICPADS-16. Wuhan, China, 2016: 826-834.
5. Jiang L, Lu H, Xu M and Wang C. Biterm Pseudo Document Topic Model for Short Text[C]. In Proceedings of ICTAI-16. San Jose, USA, 2016: 865-872.
6. Feng H, Zhang W, Wu H and Wang C. Web Page Segmentation and its Application for Web Information Crawling[C]. In Proceedings of ICTAI-16. San Jose, USA, 2016: 598-605.
7. Zhang L, Chen H, Wu J, Wang C, Xie J. False-Name-Proof Mechanisms for Path Auctions in Social Networks[C]. In Proceedings of ECAI-16. Hague, Holland, 2016: 1485-1492.
8. 刘峰,王崇骏,骆斌.一种基于最优策略概率分布的POMDP值迭代算法[J].电子学报, 2016, 44(5): 1078-1084.

2015

1. Zhang L, Wang C and Xie J. Cost optimal planning with multi valued landmarks[J]. AI Communications, 2015, 28(3): 579-590.
2. Liu F, Wang C and Luo B. PCFBPI: A point clustering feature based policy iteration algorithm[C]. In Proceedings of ICTAI-15. Vietri sul Mare, Italy, 2015: 119-124.
3. Wang Q, Li H and Wang C. Using hierarchical clustering algorithm to detect community structure in Traditional Chinese Medicine Formula network[C]. In Proceedings of ICTAI-15. Vietri sul Mare, Italy, 2015: 132-138.
4. Lu H, Chen F, Xu M, Wang C and Xie J. Never Ignore The Significance Of Different Anomalies: A Cost-sensitive Algorithm Based On Loss Function For Anomaly Detection[C]. In Proceedings of ICTAI-15. Vietri sul Mare, Italy, 2015: 1099-1105.
5. Zhan Q, Zhang J, Wang S, Yu P and Xie J. Influence Maximization Across Partially Aligned Heterogenous Social Networks[C]. In Proceedings of PAKDD-15. Ho Chi Minh City, Vietnam, 2015: 1099-1105.
6. Peng Y, Fang M, Wang C, and Xie J. Entropy Chain Multi-Label Classifiers for Traditional Medicine Diagnosing Parkinson’s Disease[C]. In Proceedings of BIBM-15. Washington DC, USA, 2015: 1722-1724.
7. Liu L, Liu M, Wang C. A low overhead storage format for SPmV on GPU systems[C]. In Proceedings of ICPADS-15. Melbourne, Australia, 2015: 733-741.

2014

1. 胡云,王崇骏,吴骏,谢俊元,李慧.微博网络上的重叠社群发现与全局表示[J].软件学报, 2014, 25(12): 2824-2836.
2. Zhang L, Wang C and Xie J. Cost optimal planning with LP-based multi-valued landmark heuristic[C]. In Proceedings of AAMAS-14. Paris, France, 2014: 509-516.
3. Yang J, Jiang L, Wang C and Xie J. Multi-Label Emotion Classification for Tweets in Weibo: Method and Application[C]. In Proceedings of ICTAI-14. Limassol, Cyprus, 2014: 424-428.
4. Liu F, Li H and Wang C. nso-HSVI: A not-so-optimistic Heuristic Search Value Iteration Algorithm for POMDPs[C]. In Proceedings of ICTAI-14. Limassol, Cyprus, 2014: 689-693.
5. Fang M, Xiao Y, Wang C and Xie J. Multi-Label classification: Dealing with Imbalance by Combining Labels[C]. In Proceedings of ICTAI-14. Limassol, Cyprus, 2014: 233-237.
6. Zhang C, Zhang L, Wang C and Xie J. Text Summarization Based on Sentence Selection with Semantic Representation[C]. In Proceedings of ICTAI-14. Limassol, Cyprus, 2014: 584-590.
7. Wu J, Wang C and Xie J. Automated Model Revision for Coordinated Open Systems[C]. In Proceedings of ICTAI-14. Limassol, Cyprus, 2014: 984-988.

2013

1. Liu Y, Pan L, Jia X, Wang C, Xie J. Three-Way Decision Based Overlapping Community Detection[C]. In Proceedings of RSKT-13. Halifax, Canada, 2013: 279-290.
2. Hu Y, Zhou Z, Xie J, Wang C. An Algorithm for Mining Top K Influential Community Based Evolutionary Outliers in Temporal Dataset[C]. In Proceedings of ICTAI-13. Washington DC, USA, 2013: 524-531.
3. Zhan Q, Yang H, Wang C, Xie J. CPP-SNS: A Solution to Influence Maximization Problem Under Cost Control[C]. In Proceedings of ICTAI-13. Washington DC, USA, 2013: 849-856.
4. Pan L, Wang C, Xie J. Spin-Glass Model based Local Community Detection Method in Social Networks[C]. In Proceedings of ICTAI-13. Washington DC, USA, 2013: 108-115.
5. Zhan Y, Wu J, Wang C, Liu M, Xie J. On the complexity of undominated core and farsighted solution concepts in coalitional games[C]. In Proceedings of AAMAS-13. Saint Paul, USA, 2013: 1177-1178.
6. Zhang L, Wang C, Wu J, Liu M, Xie J. Planning Multi-Valued Landmarks[C]. In Proceedings of AAAI-13. Bellevue, USA, 2013: 1653-1654.
7. 胡云,王崇骏,谢俊元,周作建.社群演化的稳健迁移估计及演化离群点检测[J].软件学报, 2013, 24(11): 2710-2720.

2012

1. Zhan Y, Wu J, Wang C, Liu M and Xie J. On the Complexity and Algorithms of Coalition Structure Generation in Overlapping Coalition Formation Games[C]. In Proceedings of ICTAI-12. Athens, Greece, 2012: 868-873.
2. Pan L, Dai C, Wang C, Xie J and Liu M. Overlapping Community Detection via leader-based Local Expansion in Social Networks[C]. In Proceedings of ICTAI-12. Athens, Greece, 2012: 397-404.
3. 王崇骏,吴骏,张雷等.联盟规范系统及其规范能力极限[J].软件学报, 2012, 23(7): 1796-1804.
4. 潘磊,金杰,王崇骏等.社会网络中基于局部信息的边社区挖掘[J].电子学报, 2012, 40(11): 2255-2263.

2011

1. Pan L, Wang C, Xie J, Liu M. Detecting Link Communities Based on Local Approach[C]. In Proceedings of ICTAI-11. Boca Raton, USA, 2011: 884-886.
2. Jin J, Pan L, Wang C, Xie J. A Center-based Community Detection Method In Weighted Networks[C]. In Proceedings of ICTAI-11. Boca Raton, USA, 2011: 513-518.
3. Wang C, Wu J, Wang Z, Xie J. Strategic Ability Updating in Concurrent Games by Coalitional Commitment[J]. IEEE Transactions on SMC(Part B), 2011, 41(6): 1442-1457.
4. Wu J, Wang C, Xie J. A Framework for Coalitional Normative Systems[C]. In Proceedings of AAMAS-11. Taipei, 2011: 259-266.
5. 胡云,谢俊元,王崇骏.基于组合码字的矢量量化编码算法[J].南京大学学报自然科学, 2011, 47(5): 559-565.
6. 张玉华,华浩明,范欣生,王崇骏，段金廒.基于关联规则方法探讨胸痹心痛方中十八反药对的应用规律[J].中国中药杂志, 2011, 36(24): 3544-3547.

2010

1. Zhang L, Wu J, Wang C. A Factor-Based Model for Context-Sensitive Skill Rating Systems[C]. In Proceedings of ICTAI-10. Arras, France, 2010: 249-255.
2. Zhang L, Wu J, Wang C. Multi-relational Topic Model for Social Recommendation[C]. In Proceedings of ICTAI-10. Arras, France, 2010: 349-350.
3. 韩进,蔡圣闻,王崇骏等.一种基于π^t演算的安全协议建模方法[J].计算机研究与发展, 2010, 47(4): 613-620.
4. 朱小虎,宋文军,王崇骏等.用于社团发现的Girvan-Newman改进算法[J].计算机科学与探索, 2010, 04(12): 1101-1108.
5. 宋文军,刘红星,王崇骏等.以图频繁集为基础的核心节点发现[J].计算机科学与探索, 2010, 4(1): 82-88.
6. 吴涛,王崇骏,谢俊元.基于部分可观测马尔可夫决策过程的网络入侵意图识别研究[J].南京大学学报自然科学, 2010, 46(2): 122-130.
7. 孙正,宋文军,王崇骏等.用于社团分析的差异性度量方法[J].南京大学学报自然科学, 2010, 46(5): 528-534.
8. 刘志杰,王崇骏.一个基于复合攻击路径图的报警关联算法[J].南京大学学报自然科学, 2010, 46(1): 56-63.

2009

1. Wu J, Wang C, Zhang L, et al. Coalitional planning in game-like domains via ATL model checking[C]. In Proceedings of ICTAI-09. Newark, USA, 2009: 645-652.
2. Zhou Q, Wang C, Xie J. CORE: A Trust Model for Agent Coalition Formation[C]. In Proceedings of ICNC and FSKD-09. Tianjin, China, 2009: 11-17.
3. Wu J, Wang C, Tu X, Xie J, Pu L. Temporal Reasoning in Urban Growth Simulation[C]. In Proceedings of RSKT-09. Gold Coast, Australia, 2009: 529-537.
4. Wu J, Wang C, Tu X, Xie J. On the Logic of Cellular Reactive Systems[C]. In Proceedings of IAT-09. Milan, Italy, 2009: 241-248.
5. 周清华,谢俊元,王崇骏.多Agent对抗环境下联盟形成的信任模型[J].计算机科学与探索, 2009, 3(5): 491-497.