The University of Queensland

InDISP: An Interpretable Model for Dynamic Illness Severity Prediction

Ma, Xinyu, Wang, Meng, Liu, Xing, Yang, Yifan, Zheng, Yefeng and Wang, Sen (2022). InDISP: An Interpretable Model for Dynamic Illness Severity Prediction. Database Systems for Advanced Applications. (pp. 631-638) Cham: Springer International Publishing. doi: 10.1007/978-3-031-00126-0_46

A multi-level neural network for implicit causality detection in web texts

Liang, Shining, Zuo, Wanli, Shi, Zhenkun, Wang, Sen, Wang, Junhu and Zuo, Xianglin (2022). A multi-level neural network for implicit causality detection in web texts. Neurocomputing, 481, 121-132. doi: 10.1016/j.neucom.2022.01.076

Information resilience: the nexus of responsible and agile approaches to information use

Sadiq, Shazia, Aryani, Amir, Demartini, Gianluca, Hua, Wen, Indulska, Marta, Burton-Jones, Andrew, Khosravi, Hassan, Benavides-Prado, Diana, Sellis, Timos, Someh, Ida, Vaithianathan, Rhema, Wang, Sen and Zhou, Xiaofang (2022). Information resilience: the nexus of responsible and agile approaches to information use. The VLDB Journal. doi: 10.1007/s00778-021-00720-2

Deep dynamic imputation of clinical time series for mortality prediction

Shi, Zhenkun, Wang, Sen, Yue, Lin, Pang, Lixin, Zuo, Xianglin, Zuo, Wanli and Li, Xue (2021). Deep dynamic imputation of clinical time series for mortality prediction. Information Sciences, 579, 607-622. doi: 10.1016/j.ins.2021.08.016

Scalable estimator for multi-task gaussian graphical models based in an IoT network

Wang, Beilun, Zhang, Jiaqi, Zhang, Yan, Wang, Meng and Wang, Sen (2021). Scalable estimator for multi-task gaussian graphical models based in an IoT network. ACM Transactions on Sensor Networks, 17 (3) 3432312. doi: 10.1145/3432312

Prediction of mechanical properties of wrought aluminium alloys using feature engineering assisted machine learning approach

Hu, Mingwei, Tan, Qiyang, Knibbe, Ruth, Wang, Sen, Li, Xue, Wu, Tianqi, Jarin, Sams and Zhang, Ming-Xing (2021). Prediction of mechanical properties of wrought aluminium alloys using feature engineering assisted machine learning approach. Metallurgical and Materials Transactions A: Physical Metallurgy and Materials Science, 52 (7), 2873-2884. doi: 10.1007/s11661-021-06279-5

Explaining similarity for SPARQL queries

Wang, Meng, Chen, Kefei, Xiao, Gang, Zhang, Xinyue, Chen, Hongxu and Wang, Sen (2021). Explaining similarity for SPARQL queries. World Wide Web, 24 (5), 1813-1835. doi: 10.1007/s11280-021-00886-3

Exploring BCI control in smart environments: intention recognition via EEG representation enhancement learning

Yue, Lin, Shen, Hao, Wang, Sen, Boots, Robert, Long, Guodong, Chen, Weitong and Zhao, Xiaowei (2021). Exploring BCI control in smart environments: intention recognition via EEG representation enhancement learning. ACM Transactions on Knowledge Discovery from Data, 15 (5) 3450449, 1-20. doi: 10.1145/3450449

Editorial for application-driven knowledge acquisition

Li, Xue, Wang, Sen and Li, Bohan (2020). Editorial for application-driven knowledge acquisition. World Wide Web, 23 (5), 2649-2651. doi: 10.1007/s11280-020-00827-6

Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition

Zhang, Dalin, Yao, Lina, Chen, Kaixuan, Wang, Sen, Chang, Xiaojun and Liu, Yunhao (2020). Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition. IEEE Transactions on Cybernetics, 50 (7) 8698218, 3033-3044. doi: 10.1109/TCYB.2019.2905157

A Graph-Based Hierarchical Attention Model for Movement Intention Detection from EEG Signals

Zhang, Dalin, Yao, Lina, Chen, Kaixuan, Wang, Sen, Haghighi, Pari Delir and Sullivan, Caley (2019). A Graph-Based Hierarchical Attention Model for Movement Intention Detection from EEG Signals. IEEE Transactions On Neural Systems and Rehabilitation Engineering, 27 (11) 8847648, 2247-2253. doi: 10.1109/TNSRE.2019.2943362

Compressive representation for device-free activity recognition with passive RFID signal strength

Yao, Lina, Sheng, Quan Z., Li, Xue, Gu, Tao, Tan, Mingkui, Wang, Xianzhi, Wang, Sen and Ruan, Wenjie (2018). Compressive representation for device-free activity recognition with passive RFID signal strength. IEEE Transactions On Mobile Computing, 17 (2) 7938705, 293-306. doi: 10.1109/TMC.2017.2706282

Answering why-not questions on semantic multimedia queries

Wang, Meng, Chen, Weitong, Wang, Sen, Liu, Jun, Li, Xue and Stantic, Bela (2017). Answering why-not questions on semantic multimedia queries. Multimedia Tools and Applications, 77 (3), 3405-3429. doi: 10.1007/s11042-017-5151-6

A multiview learning framework with a linear computational cost

Xue, Xiaowei, Nie, Feiping, Li, Zhihui, Wang, Sen, Li, Xue and Yao, Min (2017). A multiview learning framework with a linear computational cost. IEEE Transactions on Cybernetics, 48 (8), 2416-2425. doi: 10.1109/TCYB.2017.2739423

Collaborative text categorization via exploiting sparse coefficients

Yao, Lina, Sheng, Quan Z., Wang, Xianzhi, Wang, Shengrui, Li, Xue and Wang, Sen (2017). Collaborative text categorization via exploiting sparse coefficients. World Wide Web: internet and web information systems, 21 (2), 1-22. doi: 10.1007/s11280-017-0460-2

Learning multiple diagnosis codes for ICU patients with local disease correlation mining

Wang, 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

Diagnosis code assignment using sparsity-based disease correlation embedding

Wang, 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

Compound rank-k projections for bilinear analysis

Chang, 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

Multi-task support vector machines for feature selection with shared knowledge discovery

Wang, 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

Multi-label classification via learning a unified object-label graph with sparse representation

Yao, 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

Compact representation for large-scale unconstrained video analysis

Wang, 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

Graph-based clustering and ranking for diversified image search

Yan, 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

Structured streaming skeleton: a new feature for online human gesture recognition

Zhao, 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

Semi-supervised multiple feature analysis for action recognition

Wang, 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

Human action recognition based on semi-supervised discriminant analysis with global constraint

Zhao, Xin, Li, Xue, Pang, Chaoyi and Wang, Sen (2013). Human action recognition based on semi-supervised discriminant analysis with global constraint. Neurocomputing, 105, 45-50. doi: 10.1016/j.neucom.2012.04.038

Computing Unrestricted Synopses Under Maximum Error Bound

Pang, Chaoyi, Zhang, Qing, Zhou, Xiaofang, Hansen, David, Wang, Sen and Maeder, Anthony (2013). Computing Unrestricted Synopses Under Maximum Error Bound. Algorithmica, 65 (1), 1-42. doi: 10.1007/s00453-011-9571-9

CausalRec: causal inference for visual debiasing in visually-aware recommendation

Qiu, Ruihong, Wang, Sen, Chen, Zhi, Yin, Hongzhi and Huang, Zi (2021). CausalRec: causal inference for visual debiasing in visually-aware recommendation. MM '21: ACM Multimedia Conference, Virtual, 20-24 October 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3474085.3475266

Mitigating Generation Shifts for Generalized Zero-Shot Learning

Chen, Zhi, Luo, Yadan, Wang, Sen, Qiu, Ruihong, Li, Jingjing and Huang, Zi (2021). Mitigating Generation Shifts for Generalized Zero-Shot Learning. MM '21: ACM Multimedia Conference, Online, 20 - 24 October 2021. Washington, DC United States: Association for Computing Machinery. doi: 10.1145/3474085.3475258

Semantics disentangling for generalized zero-shot learning

Chen, Zhi, Luo, Yadan, Qiu, Ruihong, Wang, Sen, Huang, Zi, Li, Jingjing and Zhang, Zheng (2021). Semantics disentangling for generalized zero-shot learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/iccv48922.2021.00859

Self-supervised adversarial distribution regularization for medication recommendation

Wang, Yanda, Chen, Weitong, PI, Dechang, Yue, Lin, Wang, Sen and Xu, Miao (2021). Self-supervised adversarial distribution regularization for medication recommendation. Thirtieth International Joint Conference on Artificial Intelligence, Montreal, Canada, 19-27 August 2021. California, United States: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2021/431

ZSTAD: Zero-Shot Temporal Activity Detection

Zhang, Lingling, Chang, Xiaojun, Liu, Jun, Luo, Minnan, Wang, Sen, Ge, Zongyuan and Hauptmann, Alexander (2020). ZSTAD: Zero-Shot Temporal Activity Detection. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA United States, 13-19 June 2020. Piscataway, NJ United States: IEEE. doi: 10.1109/CVPR42600.2020.00096

Collective protection: Preventing sensitive inferences via integrative transformation

Zhang, Dalin, Yao, Lina, Chen, Kaixuan, Long, Guodong and Wang, Sen (2019). Collective protection: Preventing sensitive inferences via integrative transformation. 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 8-11 November 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00197

Learning attentional temporal cues of brainwaves with spatial embedding for motion intent detection

Zhang, Dalin, Chen, Kaixuan, Jian, Debao, Yao, Lina, Wang, Sen and Li, Po (2019). Learning attentional temporal cues of brainwaves with spatial embedding for motion intent detection. 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 8-11 November 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00189

Learning to hash for efficient search over incomplete knowledge graphs

Wang, Meng, Shen, Haomin, Wang, Sen, Yao, Lina, Jiang, Yinlin, Qi, Guilin and Chen, Yang (2019). Learning to hash for efficient search over incomplete knowledge graphs. 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 8-11 November 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00174

Temporal self-attention network for medical concept embedding

Peng, Xueping, Long, Guodong, Shen, Tao, Wang, Sen, Jiang, Jing and Blumenstein, Michael (2019). Temporal self-attention network for medical concept embedding. 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 8-11 November 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00060

Detecting suicidal ideation with data protection in online communities

Ji, Shaoxiong, Long, Guodong, Pan, Shirui, Zhu, Tianqing, Jiang, Jing and Wang, Sen (2019). Detecting suicidal ideation with data protection in online communities. DASFAA 2019: Database Systems for Advanced Applications , Chiang Mai, Thailand, 22-25 April, 2019. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-18590-9_17

EEG-based motion intention recognition via multi-task RNNs

Chen, Weitong, Wang, Sen, Zhang, Xiang, Yao, Lina, Yue, Lin, Qian, Buyue and Li, Xue (2018). EEG-based motion intention recognition via multi-task RNNs. 2018 SIAM International Conference on Data Mining, SDM 2018, San Diego, CA, United States, 3-5 May 2018. Society for Industrial and Applied Mathematics Publications. doi: 10.1137/1.9781611975321.32

PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linking

Wang, 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

Uncovering locally discriminative structure for feature analysis

Wang, 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

Classification based on compressive multivariate time series

Utomo, 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

Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data

Yao, 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

Learning from less for better: semi-supervised activity recognition via shared structure discovery

Yao, 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

Unobtrusive posture recognition via online learning of multi-dimensional RFID received signal strength

Yao, 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

Unsupervised feature analysis with class margin optimization

Wang, 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

Mining personal health index from annual geriatric medical examinations

Chen, Ling, Li, Xue, Wang, Sen, Hu, Hsiao-Yun, Huang, Nicole, Sheng, Quan Z. and Sharaf, Mohamed (2014). Mining personal health index from annual geriatric medical examinations. 2014 IEEE International Conference on Data Mining, Shenzhen, China, 14-17 December 2014. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDM.2014.32

Semi-supervised feature analysis for multimedia annotation by mining label correlation

Chang, Xiaojun, Shen, Haoquan, Wang, Sen, Liu, Jiajun and Li, Xue (2014). Semi-supervised feature analysis for multimedia annotation by mining label correlation. 18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014, Tainan, Taiwan, 13 - 16 May 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-06605-9_7

Effective approaches in human action recognition

Li, Xue, Sheng, Quan Z., Pang, Chaoyi, Zhao, Xin and Wang, Sen (2013). Effective approaches in human action recognition. 2013 International Conference on Advanced Computer Science and Information Systems (ICACSIS), Bali, Indonesia, 28-29 September 2013. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/ICACSIS.2013.6761544

Fall detection in multi-camera surveillance videos: experimentations and observations

Wang, Sen, Xu, Zhongwen, Yang, Yi, Li, Xue, Pang, Chaoyi and Haumptmann, Alexander G. (2013). Fall detection in multi-camera surveillance videos: experimentations and observations. 1st ACM International Workshop on Multimedia Indexing and Information Retrieval for Heathcare (MIIRH 2013), Barcelona, Spain, 22 October 2013. New York, United States: ACM. doi: 10.1145/2505323.2505331

Online action recognition by template matching

Zhao, Xin, Wang, Sen, Li, Xue and Zhang, Hao Lan (2013). Online action recognition by template matching. 2nd International Conference on Health Information Science, HIS 2013, London, United Kingdom, 25-27 March 2013. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-37899-7_25

Action recognition by exploring data distribution and feature correlation

Wang, Sen, Yang, Yi, Ma, Zhigang, Li, Xue, Pang, Chaoyi and Hauptmann, Alexander G. (2012). Action recognition by exploring data distribution and feature correlation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, United States, 16-21 June 2012. Washington, DC, United States: I E E E Computer Society. doi: 10.1109/CVPR.2012.6247823

On the prediction of re-tweeting activities in social networks – a report on WISE 2012 Challenge

Unankard, Sayan, Chen, Ling, Li, Peng, Wang, Sen, Huang, Zi, Sharaf, Mohamed A. and Li, Xue (2012). On the prediction of re-tweeting activities in social networks – a report on WISE 2012 Challenge. 13th International Conference on Web Information Systems Engineering (WISE 2012), Paphos, Cyprus, 28 - 30 November 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-35063-4_61

Effective Algorithms for Human Action Recognition

Wang, Sen (2014). Effective Algorithms for Human Action Recognition. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland.