Guansong Pang

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Chunhua ShenZhejiang UniversityVerified email at zju.edu.cn
Longbing CaoProfessor & ARC Future Fellow (Level 3), University of Technology SydneyVerified email at uts.edu.au
Anton van den HengelDirector of Applied Science at Amazon and Director of the Centre for Augmented Reasoning at AIML.Verified email at adelaide.edu.au
Ling Chenuniversity of technology sydneyVerified email at uts.edu.au
Yu TianHarvard UniversityVerified email at meei.harvard.edu
Yuanhong ChenUniversity of AdelaideVerified email at adelaide.edu.au
Gustavo CarneiroProfessor, University of AdelaideVerified email at adelaide.edu.au
Huan LiuProfessor of Computer Science and Engineering, Arizona State UniversityVerified email at asu.edu
Cheng YanBeihang UniversityVerified email at buaa.edu.cn
Xiao BaiProfessor of Computer Science, Beihang UniversityVerified email at buaa.edu.cn
Yong XiaNorthwestern Polytechnical UniversityVerified email at nwpu.edu.cn
Jun ZhouSchool of Information and Communication Technology, Griffith UniversityVerified email at griffith.edu.au
Hongzuo XuNational University of Defense TechnologyVerified email at nudt.edu.cn
Zhibin LiaoAustralian Institute for Machine Learning, University of AdelaideVerified email at adelaide.edu.au
Charu AggarwalDistinguished Research Staff Member, IBM T. J. Watson Research CenterVerified email at us.ibm.com
David AlbrechtSenior Lecturer, Monash UniversityVerified email at monash.edu
Kai Ming TingNanjing UniversityVerified email at nju.edu.cn
Choubo DingThe University of AdelaideVerified email at adelaide.edu.au
Defu Lian 连德富Professor, University of Science and Technology of ChinaVerified email at ustc.edu.cn
yuyuan liuUniversity of AdelaideVerified email at student.adelaide.edu.au

Guansong Pang

Assistant Professor of Computer Science, Singapore Management University

Verified email at smu.edu.sg - Homepage

Data Mining Machine Learning Anomaly Detection Out-of-distribution Detection Outlier Detection


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deep Learning for Anomaly Detection: A Review G Pang, C Shen, L Cao, AVD Hengel ACM Computing Surveys (CSUR) 54 (2), 1-38, 2021	613	2021
Viral Pneumonia Screening on Chest X-rays Using Confidence-Aware Anomaly Detection J Zhang, Y Xie, G Pang, Z Liao, J Verjans, W Li, Z Sun, J He, Y Li, C Shen, ... IEEE Transactions on Medical Imaging, 2020	567*	2020
An improved K-nearest-neighbor algorithm for text categorization S Jiang, G Pang, M Wu, L Kuang Expert Systems with Applications 39 (1), 1503-1509, 2012	334	2012
Deep anomaly detection with deviation networks G Pang, C Shen, A van den Hengel Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019	152	2019
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection G Pang, L Cao, L Chen, H Liu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	126	2018
Beyond triplet loss: person re-identification with fine-grained difference-aware pairwise loss C Yan, G Pang, X Bai, C Liu, X Ning, L Gu, J Zhou IEEE Transactions on Multimedia 24, 1665-1677, 2021	111	2021
Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection G Pang, C Yan, C Shen, A van den Hengel, X Bai Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020	107	2020
Outlier detection in complex categorical data by modelling feature value couplings G Pang, L Cao, L Chen Proceedings of the 25th International Joint Conference on Artificial …, 2016	58	2016
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning Y Tian, G Pang, Y Chen, R Singh, JW Verjans, G Carneiro Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021	52	2021
Sparse Modeling-based Sequential Ensemble Learning for Effective Outlier Detection in High-dimensional Numeric Data G Pang, L Cao, L Chen, D Lian, H Liu Thirty-Second AAAI Conference on Artificial Intelligence, 2018	47	2018
Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection G Pang, L Cao, L Chen, H Liu Proceedings of the Twenty-Sixth International Joint Conference on Artificial …, 2017	42	2017
Toward deep supervised anomaly detection: Reinforcement learning from partially labeled anomaly data G Pang, A van den Hengel, C Shen, L Cao Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021	40*	2021
Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings G Pang, L Cao, L Chen, H Liu 2016 IEEE 16th International Conference on Data Mining (ICDM-16), 2016	40	2016
A generalized cluster centroid based classifier for text categorization G Pang, S Jiang Information Processing & Management 49 (2), 576–586, 2013	38	2013
LeSiNN: Detecting anomalies by identifying least similar nearest neighbours G Pang, KM Ting, D Albrecht 2015 IEEE international conference on data mining workshop (ICDMW), 623-630, 2015	36	2015
Deep Weakly-supervised Anomaly Detection G Pang, C Shen, H Jin, A van den Hengel arXiv preprint arXiv:1910.13601, 2019	34*	2019
CURE: Flexible categorical data representation by hierarchical coupling learning S Jian, G Pang, L Cao, K Lu, H Gao IEEE Transactions on Knowledge and Data Engineering 31 (5), 853-866, 2019	33	2019
CenKNN: a scalable and effective text classifier G Pang, H Jin, S Jiang Data Mining and Knowledge Discovery 29 (3), 593-625, 2015	33	2015
A summary of research on automatic text classification technologies G Pang, S Jiang Information Studies: Theory & Application 2, 2012	30*	2012
A Survey of Microblog Data Mining S Jiang, Z Mai, G Pang, M Wu, L Wang Library and Information Service 56 (17), 136-142, 2012	28*	2012

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