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- affiliation: University of Technology Sydney, Australia
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2020 – today
- 2021
[j129]Can Wang, Fosca Giannotti, Longbing Cao
:
Learning Complex Couplings and Interactions. IEEE Intell. Syst. 36(1): 3-5 (2021)- [j128]Wei Wang, Longbing Cao:
VM-NSP: Vertical Negative Sequential Pattern Mining with Loose Negative Element Constraints. ACM Trans. Inf. Syst. 39(2): 22:1-22:27 (2021) - [c176]Guansong Pang, Longbing Cao, Charu Aggarwal:
Deep Learning for Anomaly Detection: Challenges, Methods, and Opportunities. WSDM 2021: 1127-1130 - [i31]Guansong Pang, Longbing Cao, Ling Chen:
Homophily Outlier Detection in Non-IID Categorical Data. CoRR abs/2103.11516 (2021) - [i30]Longbing Cao, Qing Liu, Wenfeng Hou:
COVID-19 Modeling: A Review. CoRR abs/2104.12556 (2021) - 2020
- [j127]Longbing Cao, Marley M. B. R. Vellasco:
IEEE DSAA-The IEEE Flagship Conference in Data Science [Society Briefs]. IEEE Comput. Intell. Mag. 15(3): 9-11 (2020) - [j126]Longbing Cao, George Yuan, Tim Leung, Wei Zhang:
Special Issue on AI and FinTech: The Challenge Ahead. IEEE Intell. Syst. 35(2): 3-6 (2020) - [j125]Longbing Cao, George Yuan, Tim Leung, Wei Zhang:
Special Issue on AI and FinTech: The Challenge Ahead. IEEE Intell. Syst. 35(3): 3-6 (2020) - [j124]Shoujin Wang, Gabriella Pasi, Liang Hu, Longbing Cao:
The Era of Intelligent Recommendation: Editorial on Intelligent Recommendation with Advanced AI and Learning. IEEE Intell. Syst. 35(5): 3-6 (2020) - [j123]Xiangjun Dong, Yongshun Gong, Longbing Cao:
e-RNSP: An Efficient Method for Mining Repetition Negative Sequential Patterns. IEEE Trans. Cybern. 50(5): 2084-2096 (2020) - [j122]Guansong Pang, Longbing Cao:
Heterogeneous Univariate Outlier Ensembles in Multidimensional Data. ACM Trans. Knowl. Discov. Data 14(6): 68:1-68:27 (2020) - [j121]Shoujin Wang, Longbing Cao:
Inferring Implicit Rules by Learning Explicit and Hidden Item Dependency. IEEE Trans. Syst. Man Cybern. Syst. 50(3): 935-946 (2020) - [c175]Songlei Jian, Liang Hu, Longbing Cao, Kai Lu:
Representation Learning with Multiple Lipschitz-Constrained Alignments on Partially-Labeled Cross-Domain Data. AAAI 2020: 4320-4327 - [c174]Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao:
Intention Nets: Psychology-Inspired User Choice Behavior Modeling for Next-Basket Prediction. AAAI 2020: 6259-6266 - [c173]Chengzhang Zhu, Qi Zhang, Longbing Cao, Arman Abrahamyan:
Mix2Vec: Unsupervised Mixed Data Representation. DSAA 2020: 118-127 - [c172]Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao:
Intention2Basket: A Neural Intention-driven Approach for Dynamic Next-basket Planning. IJCAI 2020: 2333-2339 - [c171]Longxiang Shi, Shijian Li, Qian Zheng, Longbing Cao, Long Yang, Gang Pan:
Maximum Entropy Reinforcement Learning with Evolution Strategies. IJCNN 2020: 1-8 - [e24]Geoffrey I. Webb, Zhongfei Zhang, Vincent S. Tseng, Graham Williams, Michalis Vlachos, Longbing Cao:
7th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2020, Sydney, Australia, October 6-9, 2020. IEEE 2020, ISBN 978-1-7281-8206-3 [contents] - [i29]Shoujin Wang, Liang Hu, Yan Wang, Longbing Cao, Quan Z. Sheng, Mehmet A. Orgun:
Sequential Recommender Systems: Challenges, Progress and Prospects. CoRR abs/2001.04830 (2020) - [i28]Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Nan Wang, Francesco Ricci, Philip S. Yu:
Graph Learning Approaches to Recommender Systems: A Review. CoRR abs/2004.11718 (2020) - [i27]Shoujin Wang, Longbing Cao, Liang Hu, Shlomo Berkovsky, Xiaoshui Huang, Lin Xiao, Wenpeng Lu:
Jointly Modeling Intra- and Inter-transaction Dependencies with Hierarchical Attentive Transaction Embeddings for Next-item Recommendation. CoRR abs/2006.04530 (2020) - [i26]Longbing Cao:
Data Science: Nature and Pitfalls. CoRR abs/2006.16964 (2020) - [i25]Longbing Cao:
Data Science: Challenges and Directions. CoRR abs/2006.16966 (2020) - [i24]Guansong Pang, Chunhua Shen, Longbing Cao, Anton van den Hengel:
Deep Learning for Anomaly Detection: A Review. CoRR abs/2007.02500 (2020) - [i23]Longbing Cao:
Data Science: A Comprehensive Overview. CoRR abs/2007.03606 (2020) - [i22]Longbing Cao:
Non-IID Recommender Systems: A Review and Framework of Recommendation Paradigm Shifting. CoRR abs/2007.07217 (2020) - [i21]Chengzhang Zhu, Longbing Cao, Jianping Yin:
Unsupervised Heterogeneous Coupling Learning for Categorical Representation. CoRR abs/2007.10720 (2020) - [i20]Longbing Cao:
AI in FinTech: A Research Agenda. CoRR abs/2007.12681 (2020) - [i19]Longbing Cao:
Coupling Learning of Complex Interactions. CoRR abs/2007.13534 (2020) - [i18]Longbing Cao:
In-Depth Behavior Understanding and Use: The Behavior Informatics Approach. CoRR abs/2007.15516 (2020) - [i17]Feng Xia, Haifeng Liu, Ivan Lee, Longbing Cao:
Scientific Article Recommendation: Exploiting Common Author Relations and Historical Preferences. CoRR abs/2008.04652 (2020) - [i16]Guansong Pang, Anton van den Hengel, Chunhua Shen, Longbing Cao:
Deep Reinforcement Learning for Unknown Anomaly Detection. CoRR abs/2009.06847 (2020)
2010 – 2019
- 2019
- [j120]Bin Guo, Yi Ouyang, Tong Guo, Longbing Cao, Zhiwen Yu:
Enhancing Mobile App User Understanding and Marketing With Heterogeneous Crowdsourced Data: A Review. IEEE Access 7: 68557-68571 (2019) - [j119]Liang Hu, Qingkui Chen, Longbing Cao, Songlei Jian, Haiyan Zhao, Jian Cao:
Evolving Coauthorship Modeling and Prediction via Time-Aware Paired Choice Analysis. IEEE Access 7: 98639-98651 (2019) - [j118]Wei Wang, Longbing Cao:
Negative Sequence Analysis: A Review. ACM Comput. Surv. 52(2): 32:1-32:39 (2019) - [j117]Shufeng Hao, Chongyang Shi, Zhendong Niu, Longbing Cao:
Modeling positive and negative feedback for improving document retrieval. Expert Syst. Appl. 120: 253-261 (2019) - [j116]Longbing Cao:
Data Science: Profession and Education. IEEE Intell. Syst. 34(5): 35-44 (2019) - [j115]Qi Zhang, Chongyang Shi, Zhendong Niu, Longbing Cao:
HCBC: A Hierarchical Case-Based Classifier Integrated with Conceptual Clustering. IEEE Trans. Knowl. Data Eng. 31(1): 152-165 (2019) - [j114]Songlei Jian, Guansong Pang, Longbing Cao, Kai Lu, Hang Gao:
CURE: Flexible Categorical Data Representation by Hierarchical Coupling Learning. IEEE Trans. Knowl. Data Eng. 31(5): 853-866 (2019) - [j113]Xiangjun Dong, Ping Qiu, Jinhu Lü, Longbing Cao, Tiantian Xu:
Mining Top- ${k}$ Useful Negative Sequential Patterns via Learning. IEEE Trans. Neural Networks Learn. Syst. 30(9): 2764-2778 (2019) - [c170]Peng Xu, Zhaohong Deng, Kup-Sze Choi, Longbing Cao, Shitong Wang:
Multi-View Information-Theoretic Co-Clustering for Co-Occurrence Data. AAAI 2019: 379-386 - [c169]Songlei Jian, Liang Hu, Longbing Cao, Kai Lu, Hang Gao:
Evolutionarily Learning Multi-Aspect Interactions and Influences from Network Structure and Node Content. AAAI 2019: 598-605 - [c168]Liang Hu, Songlei Jian, Longbing Cao, Zhiping Gu, Qingkui Chen, Artak Amirbekyan:
HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-Start Recommendation. AAAI 2019: 3830-3837 - [c167]Longxiang Shi, Shijian Li, Longbing Cao, Long Yang, Gang Pan:
TBQ(σ): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning. AAMAS 2019: 1025-1032 - [c166]Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao:
Modeling Multi-Purpose Sessions for Next-Item Recommendations via Mixture-Channel Purpose Routing Networks. IJCAI 2019: 3771-3777 - [c165]Shoujin Wang, Liang Hu, Yan Wang, Longbing Cao, Quan Z. Sheng, Mehmet A. Orgun:
Sequential Recommender Systems: Challenges, Progress and Prospects. IJCAI 2019: 6332-6338 - [i15]Shoujin Wang, Longbing Cao, Yan Wang:
A Survey on Session-based Recommender Systems. CoRR abs/1902.04864 (2019) - [i14]Longxiang Shi, Shijian Li, Longbing Cao, Long Yang, Gang Pan:
TBQ(σ): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning. CoRR abs/1905.07237 (2019) - [i13]Peng Xu, Zhaohong Deng, Kup-Sze Choi, Longbing Cao, Shitong Wang:
Multi-view Information-theoretic Co-clustering for Co-occurrence Data. CoRR abs/1905.10594 (2019) - 2018
- [j112]Shufeng Hao, Chongyang Shi, Zhendong Niu, Longbing Cao:
Concept coupling learning for improving concept lattice-based document retrieval. Eng. Appl. Artif. Intell. 69: 65-75 (2018) - [j111]Fanrong Meng, Xiaobin Rui, Zhixiao Wang, Yan Xing, Longbing Cao:
Coupled Node Similarity Learning for Community Detection in Attributed Networks. Entropy 20(6): 471 (2018) - [j110]Liang Hu, Qingkui Chen, Haiyan Zhao, Songlei Jian, Longbing Cao, Jian Cao:
Neural Cross-Session Filtering: Next-Item Prediction Under Intra- and Inter-Session Context. IEEE Intell. Syst. 33(6): 57-67 (2018) - [j109]Longbing Cao, Jae-Gil Lee, Xuemin Lin:
Introduction to the special issue on Data Science in Asia (with PAKDD'2017). Int. J. Data Sci. Anal. 6(4): 271-272 (2018) - [j108]Yi Ouyang, Bin Guo, Tong Guo, Longbing Cao, Zhiwen Yu:
Modeling and Forecasting the Popularity Evolution of Mobile Apps: A Multivariate Hawkes Process Approach. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2(4): 182:1-182:23 (2018) - [j107]Lizhen Wang, Xuguang Bao, Hongmei Chen, Longbing Cao:
Effective lossless condensed representation and discovery of spatial co-location patterns. Inf. Sci. 436-437: 197-213 (2018) - [j106]Zhaohong Deng, Junyong Chen, Te Zhang, Longbing Cao, Shitong Wang:
Generalized Hidden-Mapping Minimax Probability Machine for the training and reliability learning of several classical intelligent models. Inf. Sci. 436-437: 302-319 (2018) - [j105]Xiangjun Dong, Yongshun Gong, Longbing Cao:
F-NSP+: A fast negative sequential patterns mining method with self-adaptive data storage. Pattern Recognit. 84: 13-27 (2018) - [j104]Yonggang Huang, Longbing Cao, Jun Zhang, Lei Pan, Yuying Liu:
Exploring Feature Coupling and Model Coupling for Image Source Identification. IEEE Trans. Inf. Forensics Secur. 13(12): 3108-3121 (2018) - [j103]Can Wang, Chi-Hung Chi, Zhong She, Longbing Cao, Bela Stantic:
Coupled Clustering Ensemble by Exploring Data Interdependence. ACM Trans. Knowl. Discov. Data 12(6): 63:1-63:38 (2018) - [j102]Chengzhang Zhu, Longbing Cao, Qiang Liu, Jianping Yin, Vipin Kumar:
Heterogeneous Metric Learning of Categorical Data with Hierarchical Couplings. IEEE Trans. Knowl. Data Eng. 30(7): 1254-1267 (2018) - [j101]Songlei Jian, Longbing Cao, Kai Lu, Hang Gao:
Unsupervised Coupled Metric Similarity for Non-IID Categorical Data. IEEE Trans. Knowl. Data Eng. 30(9): 1810-1823 (2018) - [j100]Defu Lian, Kai Zheng, Yong Ge, Longbing Cao, Enhong Chen, Xing Xie:
GeoMF++: Scalable Location Recommendation via Joint Geographical Modeling and Matrix Factorization. ACM Trans. Inf. Syst. 36(3): 33:1-33:29 (2018) - [c164]Shoujin Wang, Liang Hu, Longbing Cao, Xiaoshui Huang, Defu Lian, Wei Liu:
Attention-Based Transactional Context Embedding for Next-Item Recommendation. AAAI 2018: 2532-2539 - [c163]Trong Dinh Thac Do, Longbing Cao:
Coupled Poisson Factorization Integrated With User/Item Metadata for Modeling Popular and Sparse Ratings in Scalable Recommendation. AAAI 2018: 2918-2925 - [c162]Songlei Jian, Liang Hu, Longbing Cao, Kai Lu:
Metric-Based Auto-Instructor for Learning Mixed Data Representation. AAAI 2018: 3318-3325 - [c161]Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu:
Sparse Modeling-Based Sequential Ensemble Learning for Effective Outlier Detection in High-Dimensional Numeric Data. AAAI 2018: 3892-3899 - [c160]Lizhen Wang, Xuguang Bao, Longbing Cao:
Interactive Probabilistic Post-Mining of User-Preferred Spatial Co-Location Patterns. ICDE 2018: 1256-1259 - [c159]Xingyu Chen, Fanghui Liu, Enmei Tu, Longbing Cao, Jie Yang:
Deep-PUMR: Deep Positive and Unlabeled Learning with Manifold Regularization. ICONIP (1) 2018: 12-20 - [c158]Liang Hu, Songlei Jian, Longbing Cao, Qingkui Chen:
Interpretable Recommendation via Attraction Modeling: Learning Multilevel Attractiveness over Multimodal Movie Contents. IJCAI 2018: 3400-3406 - [c157]Quangui Zhang, Longbing Cao, Chengzhang Zhu, Zhiqiang Li, Jinguang Sun:
CoupledCF: Learning Explicit and Implicit User-item Couplings in Recommendation for Deep Collaborative Filtering. IJCAI 2018: 3662-3668 - [c156]Trong Dinh Thac Do, Longbing Cao:
Metadata-dependent Infinite Poisson Factorization for Efficiently Modelling Sparse and Large Matrices in Recommendation. IJCAI 2018: 5010-5016 - [c155]Defu Lian, Kai Zheng, Vincent W. Zheng, Yong Ge, Longbing Cao, Ivor W. Tsang, Xing Xie:
High-order Proximity Preserving Information Network Hashing. KDD 2018: 1744-1753 - [c154]Guansong Pang, Longbing Cao, Ling Chen, Huan Liu:
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection. KDD 2018: 2041-2050 - [c153]Trong Dinh Thac Do, Longbing Cao:
Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence. NeurIPS 2018: 5829-5840 - [c152]Jia Xu, Longbing Cao:
Vine Copula-Based Asymmetry and Tail Dependence Modeling. PAKDD (1) 2018: 285-297 - [c151]Liying Zhang, Longbing Cao, Sheng Luo, Lei Gu, Yijin Chen, Yuanfeng Lian:
Coupled Collective Matrix Factorization. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2018: 1023-1030 - [i12]Guansong Pang, Longbing Cao, Ling Chen, Huan Liu:
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection. CoRR abs/1806.04808 (2018) - 2017
- [j99]Yunzhi Jiang, Pohsiang Tsai, Wei-Chang Yeh, Longbing Cao:
A honey-bee-mating based algorithm for multilevel image segmentation using Bayesian theorem. Appl. Soft Comput. 52: 1181-1190 (2017) - [j98]Longbing Cao:
Data science: challenges and directions. Commun. ACM 60(8): 59-68 (2017) - [j97]Longbing Cao:
Data Science: A Comprehensive Overview. ACM Comput. Surv. 50(3): 43:1-43:42 (2017) - [j96]Tingting Zhai, Yang Gao, Hao Wang, Longbing Cao:
Classification of high-dimensional evolving data streams via a resource-efficient online ensemble. Data Min. Knowl. Discov. 31(5): 1242-1265 (2017) - [j95]Shameek Ghosh, Jinyan Li, Longbing Cao, Kotagiri Ramamohanarao:
Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns. J. Biomed. Informatics 66: 19-31 (2017) - [j94]Xiangfu Meng, Longbing Cao, Xiaoyan Zhang, Jingyu Shao:
Top-k coupled keyword recommendation for relational keyword queries. Knowl. Inf. Syst. 50(3): 883-916 (2017) - [j93]Bo Liu, Yanshan Xiao, Longbing Cao:
SVM-based multi-state-mapping approach for multi-class classification. Knowl. Based Syst. 129: 79-96 (2017) - [j92]Xuhui Fan, Richard Yi Da Xu, Longbing Cao, Yin Song:
Learning Nonparametric Relational Models by Conjugately Incorporating Node Information in a Network. IEEE Trans. Cybern. 47(3): 589-599 (2017) - [j91]Liang Hu, Longbing Cao, Jian Cao, Zhiping Gu, Guandong Xu, Jie Wang:
Improving the Quality of Recommendations for Users and Items in the Tail of Distribution. ACM Trans. Inf. Syst. 35(3): 25:1-25:37 (2017) - [j90]Xiangmin Zhou, Lei Chen, Yanchun Zhang, Dong Qin, Longbing Cao, Guangyan Huang, Chen Wang:
Enhancing online video recommendation using social user interactions. VLDB J. 26(5): 637-656 (2017) - [c150]Yinghuan Shi, Wenbin Li, Yang Gao, Longbing Cao, Dinggang Shen:
Beyond IID: Learning to Combine Non-IID Metrics for Vision Tasks. AAAI 2017: 1524-1531 - [c149]Guansong Pang, Hongzuo Xu, Longbing Cao, Wentao Zhao:
Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data. CIKM 2017: 807-816 - [c148]Jia Xu, Wei Wei, Longbing Cao:
Copula-Based High Dimensional Cross-Market Dependence Modeling. DSAA 2017: 734-743 - [c147]Liang Hu, Longbing Cao, Shoujin Wang, Guandong Xu, Jian Cao, Zhiping Gu:
Diversifying Personalized Recommendation with User-session Context. IJCAI 2017: 1858-1864 - [c146]Songlei Jian, Longbing Cao, Guansong Pang, Kai Lu, Hang Gao:
Embedding-based Representation of Categorical Data by Hierarchical Value Coupling Learning. IJCAI 2017: 1937-1943 - [c145]Guansong Pang, Longbing Cao, Ling Chen, Huan Liu:
Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection. IJCAI 2017: 2585-2591 - [c144]Longbing Cao:
Behavior Informatics to Discover Behavior Insight for Active and Tailored Client Management. KDD 2017: 15-16 - [c143]Defu Lian, Rui Liu, Yong Ge, Kai Zheng, Xing Xie, Longbing Cao:
Discrete Content-aware Matrix Factorization. KDD 2017: 325-334 - [c142]Shoujin Wang, Liang Hu, Longbing Cao:
Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation. ECML/PKDD (2) 2017: 285-302 - [e23]Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin, Yang-Sae Moon:
Advances in Knowledge Discovery and Data Mining - 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part I. Lecture Notes in Computer Science 10234, 2017, ISBN 978-3-319-57453-0 [contents] - [e22]Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin, Yang-Sae Moon:
Advances in Knowledge Discovery and Data Mining - 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part II. Lecture Notes in Computer Science 10235, 2017, ISBN 978-3-319-57528-5 [contents] - 2016
- [j89]Longbing Cao, Xiangjun Dong, Zhigang Zheng:
e-NSP: Efficient negative sequential pattern mining. Artif. Intell. 235: 156-182 (2016) - [j88]Éric Gaussier, Longbing Cao:
Conference Report on 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2015) [Conference Reports]. IEEE Comput. Intell. Mag. 11(1): 13-14 (2016) - [j87]Longbing Cao:
Data Science: Nature and Pitfalls. IEEE Intell. Syst. 31(5): 66-75 (2016) - [j86]Longbing Cao:
Data science and analytics: a new era. Int. J. Data Sci. Anal. 1(1): 1-2 (2016) - [j85]Dong Li, Xianmang He, Longbing Cao, Huahui Chen:
Permutation anonymization. J. Intell. Inf. Syst. 47(3): 427-445 (2016) - [j84]Fangfang Li, Guandong Xu, Longbing Cao:
Two-level matrix factorization for recommender systems. Neural Comput. Appl. 27(8): 2267-2278 (2016) - [j83]Feng Xia, Haifeng Liu, Ivan Lee, Longbing Cao:
Scientific Article Recommendation: Exploiting Common Author Relations and Historical Preferences. IEEE Trans. Big Data 2(2): 101-112 (2016) - [j82]Liang Hu, Longbing Cao, Jian Cao, Zhiping Gu, Guandong Xu, Dingyu Yang:
Learning Informative Priors from Heterogeneous Domains to Improve Recommendation in Cold-Start User Domains. ACM Trans. Inf. Syst. 35(2): 13:1-13:37 (2016) - [j81]Zhigang Zheng, Wei Wei, Chunming Liu, Wei Cao, Longbing Cao, Maninder Bhatia:
An effective contrast sequential pattern mining approach to taxpayer behavior analysis. World Wide Web 19(4): 633-651 (2016) - [j80]Bin Shen, Longbing Cao, Min Yao, Yunjun Gao:
Mining preferred navigation patterns by consolidating both selection and time preferences. World Wide Web 19(5): 979-1007 (2016) - [c141]Karnam Dileep Kumar, Polepalli Krishna Reddy, Pailla Balakrishna Reddy, Longbing Cao:
Improving the Performance of Collaborative Filtering with Category-Specific Neighborhood. ACIIDS (2) 2016: 201-210 - [c140]Guansong Pang, Longbing Cao, Ling Chen, Huan Liu:
Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings. ICDM 2016: 410-419 - [c139]Xuhui Fan, Richard Yi Da Xu, Longbing Cao:
Copula Mixed-Membership Stochastic Blockmodel. IJCAI 2016: 1462-1468 - [c138]Guansong Pang, Longbing Cao, Ling Chen:
Outlier Detection in Complex Categorical Data by Modeling the Feature Value Couplings. IJCAI 2016: 1902-1908 - [c137]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 - 2015
- [b2]Longbing Cao:
Metasynthetic Computing and Engineering of Complex Systems. Advanced Information and Knowledge Processing, Springer 2015, ISBN 978-1-4471-6550-7, pp. 1-341 - [j79]Anna Fariha, Chowdhury Farhan Ahmed, Carson K. Leung, Md. Samiullah, Suraiya Pervin, Longbing Cao:
A new framework for mining frequent interaction patterns from meeting databases. Eng. Appl. Artif. Intell. 45: 103-118 (2015) - [j78]Wei Cao, Longbing Cao:
Financial Crisis Forecasting via Coupled Market State Analysis. IEEE Intell. Syst. 30(2): 18-25 (2015) - [j77]Longbing Cao, Philip S. Yu, Vipin Kumar:
Nonoccurring Behavior Analytics: A New Area. IEEE Intell. Syst. 30(6): 4-11 (2015) - [j76]Longbing Cao:
Coupling learning of complex interactions. Inf. Process. Manag. 51(2): 167-186 (2015) - [j75]Xiaodong Yue, Longbing Cao, Duoqian Miao, Yufei Chen, B. Xu:
Multi-view attribute reduction model for traffic bottleneck analysis. Knowl. Based Syst. 86: 1-10 (2015) - [j74]Xuhui Fan, Longbing Cao:
A convergence theorem for graph shift-type algorithms. Pattern Recognit. 48(8): 2751-2760 (2015) - [j73]Yunzhi Jiang, Pohsiang Tsai, Zhifeng Hao, Longbing Cao:
Automatic multilevel thresholding for image segmentation using stratified sampling and Tabu Search. Soft Comput. 19(9): 2605-2617 (2015) - [j72]Weiwei Liu, Zhi-Hong Deng, Longbing Cao, Xiaoran Xu, He Liu, Xiuwen Gong:
Mining Top K Spread Sources for a Specific Topic and a Given Node. IEEE Trans. Cybern. 45(11): 2472-2483 (2015) - [j71]Zhaohong Deng, Longbing Cao, Yizhang Jiang, Shitong Wang:
Minimax Probability TSK Fuzzy System Classifier: A More Transparent and Highly Interpretable Classification Model. IEEE Trans. Fuzzy Syst. 23(4): 813-826 (2015) - [j70]Philippe Fournier-Viger, Cheng-Wei Wu, Vincent S. Tseng, Longbing Cao, Roger Nkambou:
Mining Partially-Ordered Sequential Rules Common to Multiple Sequences. IEEE Trans. Knowl. Data Eng. 27(8): 2203-2216 (2015) - [j69]Can Wang, Xiangjun Dong, Fei Zhou, Longbing Cao, Chi-Hung Chi:
Coupled Attribute Similarity Learning on Categorical Data. IEEE Trans. Neural Networks Learn. Syst. 26(4): 781-797 (2015) - [j68]Xuhui Fan, Longbing Cao, Richard Yi Da Xu:
Dynamic Infinite Mixed-Membership Stochastic Blockmodel. IEEE Trans. Neural Networks Learn. Syst. 26(9): 2072-2085 (2015) - [j67]Wanqi Yang, Yang Gao, Yinghuan Shi, Longbing Cao:
MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis. IEEE Trans. Neural Networks Learn. Syst. 26(11): 2801-2815 (2015) - [j66]