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2017 Journal Article Learning multiple diagnosis codes for ICU patients with local disease correlation miningWang, Sen, Li, Xue, Chang, Xiaojun, Yao, Lina, Sheng, Quan Z. and Long, Guodong (2017). Learning multiple diagnosis codes for ICU patients with local disease correlation mining. ACM Transactions on Knowledge Discovery from Data, 11 (3) 31, 1-21. doi: 10.1145/3003729 |
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2017 Conference Publication Improving chinese sentiment analysis via segmentation-based representation using parallel CNNHao, Yazhou, Zheng, Qinghua, Lan, Yangyang, Li, Yufei, Wang, Meng, Wang, Sen and Li, Chen (2017). Improving chinese sentiment analysis via segmentation-based representation using parallel CNN. 13th International Conference on Advanced Data Mining and Applications ADMA 2017, Singapore, 5–6 November 2017. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-69179-4_47 |
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2017 Conference Publication Uncovering locally discriminative structure for feature analysisWang, Sen, Nie, Feiping, Chang, Xiaojun, Li, Xue, Sheng, Quan Z. and Yao, Lina (2017). Uncovering locally discriminative structure for feature analysis. 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016, Riva del Garda, Italy, 19 - 23 September 2016. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-46128-1_18 |
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2017 Conference Publication Provenance-based rumor detectionDuong, Chi Thang, Nguyen, Quoc Viet Hung, Wang, Sen and Stantic, Bela (2017). Provenance-based rumor detection. 28th Australasian Database Conference, ADC 2017, Brisbane, QLD Australia, 25–28 September 2017. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-68155-9_10 |
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2017 Conference Publication Multi-view correlated feature learning by uncovering shared componentXue, Xiaowei, Nie, Feiping, Wang, Sen, Chang, Xiaojun, Stantic, Bela and Yao, Min (2017). Multi-view correlated feature learning by uncovering shared component. 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, CA United States, 4–9 February 2017. Washington, DC United States: AAAI Press. doi: 10.1609/aaai.v31i1.10823 |
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2017 Conference Publication PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linkingWang, Meng, Zhang, Jiaheng, Liu, Jun, Hu, Wei, Wang, Sen, Li, Xue and Liu, Wenqiang (2017). PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linking. The Semantic Web – ISWC 2017: 16th International Semantic Web Conference Vienna, Austria, October 21–25, 2017 Proceedings, Part II, Vienna, Austria, 21-25 October 2017. Cham, Switzerland: Springer Nature. doi: 10.1007/978-3-319-68204-4_23 |
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2016 Journal Article Diagnosis code assignment using sparsity-based disease correlation embeddingWang, Sen, Chang, Xiaojun, Li, Xue, Long, Guodong, Yao, Lina and Sheng, Quan Z. (2016). Diagnosis code assignment using sparsity-based disease correlation embedding. IEEE Transactions on Knowledge and Data Engineering, 28 (12), 3191-3202. doi: 10.1109/TKDE.2016.2605687 |
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2016 Journal Article Compound rank-k projections for bilinear analysisChang, Xiaojun, Nie, Feiping, Wang, Sen, Yang, Yi, Zhou, Xiaofang and Zhang, Chengqi (2016). Compound rank-k projections for bilinear analysis. IEEE Transactions on Neural Networks and Learning Systems, 27 (7) 7161356, 1502-1513. doi: 10.1109/TNNLS.2015.2441735 |
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2016 Journal Article Multi-task support vector machines for feature selection with shared knowledge discoveryWang, Sen, Chang, Xiaojun, Li, Xue, Sheng, Quan Z. and Chen, Weitong (2016). Multi-task support vector machines for feature selection with shared knowledge discovery. Signal Processing, 120, 746-753. doi: 10.1016/j.sigpro.2014.12.012 |
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2016 Conference Publication Learning from less for better: semi-supervised activity recognition via shared structure discoveryYao, Lina, Nie, Feiping, Sheng, Quan Z., Gu, Tao, Li, Xue and Wang, Sen (2016). Learning from less for better: semi-supervised activity recognition via shared structure discovery. 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016, Heidelberg, Germany, 12-16 September 2016. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2971648.2971701 |
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2016 Conference Publication Learning graph-based POI embedding for location-based recommendationXie, Min, Yin, Hongzhi, Wang, Hao, Xu, Fanjiang, Chen, Weitong and Wang, Sen (2016). Learning graph-based POI embedding for location-based recommendation. 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, United States, 24 - 28 October 2016. New York, NY, United States: ACM. doi: 10.1145/2983323.2983711 |
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2016 Conference Publication Unobtrusive posture recognition via online learning of multi-dimensional RFID received signal strengthYao, Lina, Sheng, Quan Z., Ruan, Wenjie, Li, Xue, Wang, Sen and Yang, Zhi (2016). Unobtrusive posture recognition via online learning of multi-dimensional RFID received signal strength. 2015 IEEE 21st International Conference on Parallel and Distributed Systems, ICPADS 2015, Melbourne, Victoria, Australia, 14- 17 December 2015. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPADS.2015.23 |
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2016 Conference Publication Classification based on compressive multivariate time seriesUtomo, Chandra, Li, Xue and Wang, Sen (2016). Classification based on compressive multivariate time series. 27th Australasian Database Conference on Databases Theory and Applications, ADC 2016, Sydney Australia, 28-29 September 2016. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-46922-5_16 |
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2016 Conference Publication Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing dataYao, Lina, Sheng, Quan Z., Li, Xue, Wang, Sen, Gu, Tao, Ruan, Wenjie and Zou, Wan (2016). Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data. 15th IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, United States, 14-17 November 2015. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDM.2015.102 |
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2015 Journal Article Multi-label classification via learning a unified object-label graph with sparse representationYao, Lina, Sheng, Quan Z., Ngu, Anne H.H., Gao, Byron J., Li, Xue and Wang, Sen (2015). Multi-label classification via learning a unified object-label graph with sparse representation. World Wide Web, 19 (6), 1-25. doi: 10.1007/s11280-015-0376-7 |
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2015 Journal Article Compact representation for large-scale unconstrained video analysisWang, Sen, Pan, Pingbo, Long, Guodong, Chen, Weitong, Li, Xue and Sheng, Quan Z. (2015). Compact representation for large-scale unconstrained video analysis. World Wide Web, 19 (2), 231-246. doi: 10.1007/s11280-015-0354-0 |
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2015 Conference Publication Unsupervised feature analysis with class margin optimizationWang, Sen, Nie, Feiping, Chang, Xiaojun, Yao, Lina, Li, Xue and Sheng, Quan Z. (2015). Unsupervised feature analysis with class margin optimization. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Porto, Portugal, 7-11 September 2015. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-23528-8_24 |
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2014 Journal Article Graph-based clustering and ranking for diversified image searchYan, Yan, Liu, Gaowen, Wang, Sen, Zhang, Jian and Zheng, Kai (2014). Graph-based clustering and ranking for diversified image search. Multimedia Systems, 23 (1), 41-52. doi: 10.1007/s00530-014-0419-4 |
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2014 Journal Article Structured streaming skeleton: a new feature for online human gesture recognitionZhao, Xin, Li, Xue, Pang, Chaoyi, Sheng, Quan Z., Wang, Sen and Ye, Mao (2014). Structured streaming skeleton: a new feature for online human gesture recognition. ACM Transactions on Multimedia Computing, Communications and Applications, 11 (Supp. 1s) 22, 22:1-22:18. doi: 10.1145/2648583 |
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2014 Journal Article Semi-supervised multiple feature analysis for action recognitionWang, Sen, Ma, Zhigang, Yang, Yi, Li, Xue, Pang, Chaoyi and Hauptmann, Alexander G. (2014). Semi-supervised multiple feature analysis for action recognition. IEEE Transactions on Multimedia, 16 (2) 6675840, 289-298. doi: 10.1109/TMM.2013.2293060 |
