科研进展

来自南京大学IIP
Iip1314（讨论 | 贡献）2022年11月19日 (六) 21:37的版本
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研究成果

Selected Paper

2022

  1. 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, Accepted
  2. 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, Accepted
  3. Zhang B., etc. CopGAT: Co-propagation Self-supervised Graph Attention Network. In Proceedings of ISPA 2022, Accepted
  4. Yu H., etc. DIPool: Degree-Induced Pooling for Hierarchical Graph Representation Learning. In Proceedings of ISPA 2022, Accepted
  5. 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，录用
  6. MA C., etc. Unsupervised Point Cloud Completion and Segmentation by Generative Adversarial Autoencoding Network[C]. In Proceedings of  NIPS 2022, Accepted 
  7. Liu Z., etc. FIXC: A Method for Data Distribution Shifts Calibration via Feature Importance[C].  In Proceedings of ICTAI 2022, Accepted
  8. Ge Y., etc. MRM: Site Selection via Mutil-round Meanshift for Global Fairness[C].  In Proceedings of ICTAI 2022, Accepted
  9. Yu H., etc. Not All Edges are Peers: Accurate Structure-Aware Graph Pooling Networks[J]. Neural Networks, Accepted
  10. 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, Accepted
  11. 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
  12. Wu J., Cao J., Sun H., and Wang C. A Bayesian Optimal Social Law Synthesizing Mechanism for Strategic Agents[J]. JAAMAS, 2022, 36(2)
  13. 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, Accepted
  14. Xu M. etc. NED-GNN: Detecting and Dropping Noisy Edges in Graph Neural Networks[C]. In Proceedings of  APWeb-WAIM 2022, Accepted
  15. Xu M. etc. NC-GNN: Consistent Neighbors of Nodes Help More in Graph Neural Networks[J].Wireless Communications and Mobile Computing, Accepted
  16. 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, Accepted
  17. 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
  18. Zhang Y. Zhu Y., Zhang Z., Wang C. Collaboration based Multi-modal Multi-label Learning[J]. Applied Intelligence,2022, 52(12): 14204-14217
  19. Zhang Y. Chen M. Shen J. Wang C. Tailor Versatile Multi-modal Learning for Multi-label Emotion Recognition. In Proceedings of  AAAI2022, 9100-9108
  20. Chen M. Du Y., Zhang Y., Qian S. Wang C. Semi-Supervised Learning with Multi-Head Co-Training. In Proceedings of  AAAI2022, 6278- 6286
  21. Jinliang Yuan, Yirong Yao,  Ming Xu, Hualei Yu, Junyuan Xie and Chongjun Wang.Graph Structure Learning based on Feature[J].IDA Journal, Accepted
  22. 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
  23. 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
  24. 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.
取自“http://iip.nju.edu.cn/index.php?title=科研进展&oldid=1710”