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Anomaly detection (AD) plays a pivotal role in numerous web-based applications, including malware detection, anti-money laundering, device failure detection, and network fault analysis.
Nearest neighbor pattern classification
Thomas Cover and Peter Hart. 1967 · 1967
Earlier work this paper cites.
Classification and regression trees (Wadsworth, Belmont, CA)
L Breiman, JH Friedman, RA Olshen, and CJ Stone. 1984 · 1984
Earlier work this paper cites.
Simplifying decision trees
J. Ross Quinlan. 1987 · 1987
Earlier work this paper cites.
Statlog (Landsat Satellite)
Ashwin Srinivasan. 1993 · 1993
Earlier work this paper cites.
Support vector machine
Corinna Cortes and Vladimir Vapnik. 1995 · 1995
Earlier work this paper cites.
Spambase
Mark Hopkins, Erik Reeber, George Forman, and Jaap Suermondt. 1999 · 1999
Earlier work this paper cites.
SisPorto 2.0: a program for automated analysis of cardiotocograms
Diogo Ayres-de Campos, Joao Bernardes, Antonio Garrido, Joaquim Marques-de Sa, and Luis Pereira-Leite. 2000 · 2000
Earlier work this paper cites.
Decomposable negation normal form
Adnan Darwiche. 2001a · 2001
Earlier work this paper cites.
On the tractable counting of theory models and its application to truth maintenance and belief revision
Adnan Darwiche. 2001b · 2001
Earlier work this paper cites.
A knowledge compilation map
Adnan Darwiche and Pierre Marquis. 2002 · 2002
Earlier work this paper cites.
New Advances in Compiling CNF to Decomposable Negation Normal Form. In Proceedings of the 16th European Conference on Artificial Intelligence (Valencia, Spain) (ECAI’04) . IOS Press, NLD, 318–322
Adnan Darwiche. 2004 · 2004
Earlier work this paper cites.
Propositional Logic
Kevin C. Klement. 2004 · 2004
Earlier work this paper cites.
Neural networks vs. decision trees for intrusion detection. In IEEE/IST workshop on monitoring, attack detection and mitigation (MonAM) , Vol. 28. 29
Yacine Bouzida and Frederic Cuppens. 2006 · 2006
Earlier work this paper cites.
Introduction to Mathematical Logic
Vilnis Detlovs and Karlis Podnieks. 2011 · 2011
Earlier work this paper cites.
Scikit-learn: Machine Learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. 2011 · 2011
Earlier work this paper cites.
Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi. 2013 · 2013
Earlier work this paper cites.
From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews. In Proceedings of the 22nd international conference on World Wide Web . 897–908
Julian John McAuley and Jure Leskovec. 2013 · 2013
Earlier work this paper cites.
Adam: a method for stochastic optimization. In The 3rd International Conference on Learning Representations
DP Kingma. 2015 · 2015
Earlier work this paper cites.
Collective opinion spam detection: Bridging review networks and metadata. In Proceedings of the 21th acm sigkdd international conference on knowledge discovery and data mining . 985–994
Shebuti Rayana and Leman Akoglu. 2015 · 2015
Earlier work this paper cites.
Incorporating expert feedback into active anomaly discovery. In 2016 IEEE 16th International Conference on Data Mining (ICDM) . IEEE, 853–858
Shubhomoy Das, Weng-Keen Wong, Thomas Dietterich, Alan Fern, and Andrew Emmott. 2016 · 2016
Earlier work this paper cites.
Stochastic optimization for large-scale optimal transport
Aude Genevay, Marco Cuturi, Gabriel Peyré, and Francis Bach. 2016 · 2016
Earlier work this paper cites.
Relational restricted boltzmann machines: A probabilistic logic learning approach. In Inductive Logic Programming: 27th International Conference, ILP 2017, Orléans, France, September 4-6, 2017, Revised Selected Papers 27 . Springer, 94–111
Navdeep Kaur, Gautam Kunapuli, Tushar Khot, Kristian Kersting, William Cohen, and Sriraam Natarajan. 2018 · 2017
Earlier work this paper cites.
Semi-Supervised Classification with Graph Convolutional Networks. In International Conference on Learning Representations
Thomas N. Kipf and Max Welling. 2017 · 2017
Earlier work this paper cites.
Ganomaly: Semi-supervised anomaly detection via adversarial training. In Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers, Part III 14 . Springer, 622–637
Samet Akcay, Amir Atapour-Abarghouei, and Toby P Breckon. 2019 · 2018
Cited alongside, same era.
Deep one-class classification. In International conference on machine learning . PMLR, 4393–4402
Lukas Ruff, Robert Vandermeulen, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel Müller, and Marius Kloft. 2018 · 2018
Cited alongside, same era.
Lifted relational neural networks: Efficient learning of latent relational structures
Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezny, Steven Schockaert, and Ondrej Kuzelka. 2018 · 2018
Cited alongside, same era.
IDEA: Intrusion detection through electromagnetic-signal analysis for critical embedded and cyber-physical systems
Haider Adnan Khan, Nader Sehatbakhsh, Luong N Nguyen, Robert L Callan, Arie Yeredor, Milos Prvulovic, and Alenka Zajić. 2019 · 2019
Cited alongside, same era.
A dual-system method for intelligent fault localization in communication networks. In ICC 2022-IEEE International Conference on Communications . IEEE, 4062–4067
Jinglong Ji, Fujin Zhu, Jiaxu Cui, Haihong Zhao, and Bo Yang. 2022 · 2022
Later among the works it cites.
Semi-supervised hierarchical graph classification
Jia Li, Yongfeng Huang, Heng Chang, and Yu Rong. 2022a · 2022
Later among the works it cites.
Dual-MGAN: An Efficient Approach for Semi-supervised Outlier Detection with Few Identified Anomalies
Zhe Li, Chunhua Sun, Chunli Liu, Xiayu Chen, Meng Wang, and Yezheng Liu. 2022b · 2022
Later among the works it cites.
Dual-MGAN: An Efficient Approach for Semi-supervised Outlier Detection with Few Identified Anomalies
Zhe Li, Chunhua Sun, Chunli Liu, Xiayu Chen, Meng Wang, and Yezheng Liu. 2022c · 2022
Later among the works it cites.
A Logic Aware Neural Generation Method for Explainable Data-to-text. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 3318–3326
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Vessel optimal transport for automated alignment of retinal fundus images
Danilo Motta, Wallace Casaca, and Afonso Paiva. 2019 · 2019
Cited alongside, same era.
Deep anomaly detection with deviation networks. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining . 353–362
Guansong Pang, Chunhua Shen, and Anton van den Hengel. 2019 · 2019
Cited alongside, same era.
Deep Semi-Supervised Anomaly Detection. In International Conference on Learning Representations
Lukas Ruff, Robert A Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, and Marius Kloft. 2019 · 2019
Cited alongside, same era.
Embedding symbolic knowledge into deep networks
Yaqi Xie, Ziwei Xu, Mohan S Kankanhalli, Kuldeep S Meel, and Harold Soh. 2019a · 2019
Cited alongside, same era.
Optimal transport graph neural networks. In International Conference on Learning Representations
Gary Bécigneul, Octavian-Eugen Ganea, Benson Chen, Regina Barzilay, and Tommi S Jaakkola. 2020 · 2020
Cited alongside, same era.
Esad: End-to-end deep semi-supervised anomaly detection
Chaoqin Huang, Fei Ye, Peisen Zhao, Ya Zhang, Yan-Feng Wang, and Qi Tian. 2020 · 2020
Cited alongside, same era.
Autoaudit: Mining accounting and time-evolving graphs. In 2020 IEEE International Conference on Big Data (Big Data) . IEEE, 950–956
Meng-Chieh Lee, Yue Zhao, Aluna Wang, Pierre Jinghong Liang, Leman Akoglu, Vincent S Tseng, and Christos Faloutsos. 2020 · 2020
Cited alongside, same era.
Interpretable, multidimensional, multimodal anomaly detection with negative sampling for detection of device failure. In International Conference on Machine Learning . PMLR, 9016–9025
John Sipple. 2020 · 2020
Cited alongside, same era.
Xiexiong Lin, Huaisong Li, Tao Huang, Feng Wang, Linlin Chao, Fuzhen Zhuang, Taifeng Wang, and Tianyi Zhang. 2022 · 2022
Later among the works it cites.
Rethinking graph neural networks for anomaly detection. In International Conference on Machine Learning . PMLR, 21076–21089
Jianheng Tang, Jiajin Li, Ziqi Gao, and Jia Li. 2022 · 2022
Later among the works it cites.
Anomaly detection by leveraging incomplete anomalous knowledge with anomaly-aware bidirectional gans
Bowen Tian, Qinliang Su, and Jian Yin. 2022 · 2022
Later among the works it cites.
Multi-granularity cross-modal alignment for generalized medical visual representation learning
Fuying Wang, Yuyin Zhou, Shujun Wang, Varut Vardhanabhuti, and Lequan Yu. 2022 · 2022
Later among the works it cites.
Deep Insights into Noisy Pseudo Labeling on Graph Data. In Thirty-seventh Conference on Neural Information Processing Systems
WANG Botao, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, and Fugee Tsung. 2023 · 2023
Later among the works it cites.
Anti-Money Laundering by Group-Aware Deep Graph Learning
Dawei Cheng, Yujia Ye, Sheng Xiang, Zhenwei Ma, Ying Zhang, and Changjun Jiang. 2023 · 2023
Later among the works it cites.
Weakly supervised anomaly detection: A survey
Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S Yu, and Yue Zhao. 2023b · 2023
Later among the works it cites.
Diga: Guided Diffusion Model for Graph Recovery in Anti-Money Laundering. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 4404–4413
Xujia Li, Yuan Li, Xueying Mo, Hebing Xiao, Yanyan Shen, and Lei Chen. 2023 · 2023
Later among the works it cites.
Deep weakly-supervised anomaly detection. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 1795–1807
Guansong Pang, Chunhua Shen, Huidong Jin, and Anton van den Hengel. 2023 · 2023
Later among the works it cites.
All in One: Multi-Task Prompting for Graph Neural Networks. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining (KDD’23) . 2120–2131
Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, and Jihong Guan. 2023 · 2023
Later among the works it cites.
Robust Attributed Graph Alignment via Joint Structure Learning and Optimal Transport. In 2023 IEEE 39th International Conference on Data Engineering (ICDE) . 1638–1651
Jianheng Tang, Weiqi Zhang, Jiajin Li, Kangfei Zhao, Fugee Tsung, and Jia Li. 2023b · 2023
Later among the works it cites.
A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment. In Findings of the Association for Computational Linguistics: ACL 2023 . Toronto, Canada, 3320–3334
Jianheng Tang, Kangfei Zhao, and Jia Li. 2023c · 2023
Later among the works it cites.
Deep Isolation Forest for Anomaly Detection
Hongzuo Xu, Guansong Pang, Yijie Wang, and Yongjun Wang. 2023 · 2023
Later among the works it cites.
A survey on neural-symbolic learning systems
Dongran Yu, Bo Yang, Dayou Liu, Hui Wang, and Shirui Pan. 2023 · 2023
Later among the works it cites.
PARROT: Position-Aware Regularized Optimal Transport for Network Alignment. In Proceedings of the ACM Web Conference 2023 . 372–382
Zhichen Zeng, Si Zhang, Yinglong Xia, and Hanghang Tong. 2023 · 2023
Later among the works it cites.
Effective Fault Scenario Identification for Communication Networks Via Knowledge-Enhanced Graph Neural Networks
Haihong Zhao, Bo Yang, Jiaxu Cui, Qianli Xing, Jiaxing Shen, Fujin Zhu, and Jiannong Cao. 2023 · 2023
Later among the works it cites.
Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, Cristian Lumezanu, Daeki Cho, and Haifeng Chen. 2018 · 2023
Later among the works it cites.
Learning representations of ultrahigh-dimensional data for random distance-based outlier detection. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining . 2041–2050
Guansong Pang, Longbing Cao, Ling Chen, and Huan Liu. 2018 · 2050
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