A survey on unsupervised outlier detection in high‐dimensional numerical data

Zimek, Arthur, Schubert, Erich, Kriegel, Hans‐Peter·2012·Statistical Analysis and Data Mining The ASA Data Science Journal
DOI 10.1002/sam.11161

Cited by (854)

Items 701–800 of 854

  1. Reconstruct Anomaly to Normal: Adversarial Learned and Latent Vector-constrained Autoencoder for Time-series Anomaly Detection
    Chunkai Zhang, Zuo, Wei, Xuan Wang · 2020 · arXiv (Cornell University)
  2. Robust Deep Learning on Graphs
    Vasileios Ioannidis · 2020
  3. Condition Monitoring of Rotating Machines in Power Generation Plants
    Aldo Dagnino · 2021 · Springer eBooks
  4. WITHDRAWN: Detecting the outliers in high dimensional datasets using poisson regression
    Peruri Venkata Anusha, Ch. Anuradha, P. S. Murthy, Surya Kiran Chebrolu · 2021 · Materials Today Proceedings · Retracted
  5. Abrupt covariance based signal extraction for fault prediction of an aircraft engine
    Sujeong Baek, Yong-Uk Song · 2021 · ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter)
  6. Robust selection of predictors and conditional outlier detection in a perturbed large-dimensional regression context
    Matteo Farnè, Angelos T. Vouldis · 2021 · arXiv (Cornell University)
  7. Using Similarity Self-Join Techniques
    Eugenio Ferreira Cabral · 2021 · Digital Library of Theses and Dissertations (Universidade de São Paulo)
  8. A Fully Automatic and Efficient Methodology for Peptide Activity Identification Using Their 3D Conformations
    Azzam Alwan, Rémi Cogranne, Pierre Beauseroy, Edith Grall‐Maës, Nicolas Belloy, Laurent Debelle, Stéphanie Baud, Manuel Dauchez, Sébastien Almagro · 2021 · IEEE Access
  9. High-Resolution Neural Style Transfer for Test Data Generation for ADAS/HAD Functions
    Andrej Junginger, Markus Hanselmann, Thilo Strauss, Sebastian Boblest, Jens S. Buchner, Holger Ulmer · 2021 · Proceedings
  10. Automated machine learning for supervised and unsupervised models with artificial neural networks
    Alireza Naghizadeh Nohadani · 2021
  11. On Methods and Measures for the Inspection of Arbitrarily Oriented Subspace Clusters
    Daniyal Kazempour, Johannes Winter, Peer Kröger, Thomas Seidl · 2021 · Datenbank-Spektrum
  12. A moment-matching metric for latent variable generative models
    Cédric Beaulac · 2023 · Machine Learning
  13. Latent-Insensitive Autoencoders for Anomaly Detection
    Muhammad S. Battikh, Artem A. Lenskiy · 2021 · Mathematics
  14. Peer Review #1 of "NFAD: fixing anomaly detection using normalizing flows (v0.1)"
    2021 · PeerJ Computer Science
  15. Peer Review #1 of "NFAD: fixing anomaly detection using normalizing flows (v0.2)"
    2021 · PeerJ Computer Science
  16. Peer Review #2 of "NFAD: fixing anomaly detection using normalizing flows (v0.1)"
    2021 · PeerJ Computer Science
  17. Outlier Detection and Abnormal Subspace Search Based on Autoencoder and Genetic Algorithm for High-Dimensional Data
    Jiamu Li, Ji Zhang, Jian Wang, Youwen Zhu, Mohamed Jaward Bah, Gaoming Yang, Yuquan Gan · 2021 · IEEE International Conference on Computer and Communications (ICCC)
  18. An Extensive Survey on Outlier Prediction Using Mining and Learning Approaches
    Chigurupati Ravi Swaroop, K. Raja, M. S. Babu · 2022 · Lecture notes on data engineering and communications technologies
  19. lifecycle
    Robin Hanson · 2016 · Oxford University Press eBooks
  20. Collaboration
    Robin Hanson · 2016 · Oxford University Press eBooks
  21. Conflict
    Robin Hanson · 2016 · Oxford University Press eBooks
  22. Politics
    Robin Hanson · 2016 · Oxford University Press eBooks
  23. Faculty Opinions recommendation of The heterogeneity problem: approaches to identify psychiatric subtypes.
    Vikram Patel · 2019 · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature
  24. Growth
    Robin Hanson · 2016 · Oxford University Press eBooks
  25. Start
    Robin Hanson · 2016 · Oxford University Press eBooks
  26. Farewells
    Robin Hanson · 2016 · Oxford University Press eBooks
  27. Society
    Robin Hanson · 2016 · Oxford University Press eBooks
  28. Appearances
    Robin Hanson · 2016 · Oxford University Press eBooks
  29. Implementation
    Robin Hanson · 2016 · Oxford University Press eBooks
  30. Business
    Robin Hanson · 2016 · Oxford University Press eBooks
  31. clumping
    Robin Hanson · 2016 · Oxford University Press eBooks
  32. Efficiency
    Robin Hanson · 2016 · Oxford University Press eBooks
  33. Existence
    Robin Hanson · 2016 · Oxford University Press eBooks
  34. Bibliography
    2017 · Elsevier eBooks
  35. Framing
    Robin Hanson · 2016 · Oxford University Press eBooks
  36. Signals
    Robin Hanson · 2016 · Oxford University Press eBooks
  37. Fast and Scalable Outlier Detection with Metric Access Methods
    Altamir Gomes Bispo · 2019
  38. Mating
    Robin Hanson · 2016 · Oxford University Press eBooks
  39. Sample Handling and Automation: Outlier
    Piyushkumar A. Mundra, Kevin Huynh, Peter J. Meikle · 2015 · Springer eBooks
  40. Assumptions
    Robin Hanson · 2016 · Oxford University Press eBooks
  41. Infrastructure
    Robin Hanson · 2016 · Oxford University Press eBooks
  42. labor
    Robin Hanson · 2016 · Oxford University Press eBooks
  43. Minds
    Robin Hanson · 2016 · Oxford University Press eBooks
  44. Rules
    Robin Hanson · 2016 · Oxford University Press eBooks
  45. Modes
    Robin Hanson · 2016 · Oxford University Press eBooks
  46. Variations
    Robin Hanson · 2016 · Oxford University Press eBooks
  47. Groups
    Robin Hanson · 2016 · Oxford University Press eBooks
  48. choices
    Robin Hanson · 2016 · Oxford University Press eBooks
  49. Introduction
    Robin Hanson · 2016 · Oxford University Press eBooks
  50. Scales
    Robin Hanson · 2016 · Oxford University Press eBooks
  51. Finale
    Robin Hanson · 2016 · Oxford University Press eBooks
  52. A Protocol for Creating and Modifying the Outlier Detection System's General Framework
    D. Divya, M. Bhasi, M. B. Santoshkumar · 2022 · Research Square
  53. Reconstruction-Based One-Class Classification Anomaly Detection for Tabular Data
    Jianan Lü, Wei Li, Yue Zhao · 2022 · Communications in computer and information science
  54. A Protocol for Creating and Modifying the Outlier Detection System's General Framework
    D. Divya, M. Bhasi, M. B. Santoshkumar · 2022 · Research Square
  55. INVESTIGATIONS OF AUTOENCODER HYPER-PARAMETERS ON ANOMALY DETECTION
    Van Loi Cao · 2021 · Journal of Science and Technique
  56. A Novel Semi-supervised Clustering Algorithm: CoExDBSCAN
    Benjamin Ertl, Matthias F. Schneider, Jörg Meyer, Achim Streit · 2022 · Communications in computer and information science
  57. ITL: An Isolation-Tree-Based Learning of Features for Anomaly Detection in Networked Systems
    Sara Kardani Moghaddam, Rajkumar Buyya, Kotagiri Ramamohanarao · 2022 · Internet of things
  58. Deep Metric Learning
    Avik Santra, Souvik Hazra, Lorenzo Servadei, Thomas Stadelmayer, Michael Stephan, Anand Dubey · 2022
  59. Orthogonal Multi-frequency Fusion Based Image Reconstruction and Diagnosis in Diffuse Optical Tomography
    Hanene Ben Yedder, Ghassan Hamarneh, Ben Cardoen, Majid Shokoufi, Farid Golnaraghi · 2022
  60. Random Projection and Recovery for High Dimensional Optimization with Arbitrary Outliers
    Jiawei Huang, Ruizhe Qin, Fan Yang, Hu Ding · 2022 · International Journal of Computational Geometry & Applications
  61. An outlier detection method with CNN for BeiDou MEO moderate-energy electron data
    Chao Tian, Cui Ruifei, Riwei Zhang, Peikang Xu, Libo Chen, Jie Shang, Quan Lin, Yujun Wan, Sihui Hu, Fulu Yue et al. · 2023 · Open Astronomy
  62. Machine learning application in modelling marine and coastal phenomena: a critical review
    Ali Pourzangbar, Mahdi Jalali, Maurizio Brocchini · 2023 · SSRN Electronic Journal
  63. Detailed Process for Developing an Efficient Anomaly Detection Algorithm for Real-Time Streaming Data in Large-Scale Industrial Systems
    Rakesh Kumar Sen · 2023 · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
  64. Deep Orthogonal Multi-Frequency Fusion for Tomogram-Free Diagnosis in Diffuse Optical Imaging
    Hanene Ben Yedder, Ghassan Hamarneh, Ben Cardoen, Majid Shokoufi, Farid Golnaraghi · 2023
  65. Relative density clouds: Visualizing and exploring multivariate patterns of group differences
    Marco Del Giudice · 2023 · PLoS ONE
  66. Multi-aspect Data Learning: Overview, Challenges and Approaches
    Richi Nayak, Khanh Luong · 2023 · Intelligent systems reference library
  67. Sensor Virtualization for Anomaly Detection of Turbo-Machinery Sensors—An Industrial Application
    Sachin Shetty, V. Gori, Gianni Bagni, Giacomo Veneri · 2023 · International Conference on Time Series and Forecasting (ITISE)
  68. Non-technical loss detection in power grids based on time series representations
    Agnaldo Aparecido Esmael · 2021
  69. Novel Relation Detection: Discovering Unknown Relation Types via Multi-Strategy Self-Supervised Learning
    Qingbin Liu, Y.-J. Chen Y.-S. Kung, Yanchao Hao, Dianbo Sui, Siyuan Cheng, Xi Chen, Ningyu Zhang, Jiaoyan Chen · 2023 · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)
  70. Associating Anomaly Detection Strategy Based on Kittler’s Taxonomy with Image Editing to Extend the Mapping of Polluted Water Bodies
    Giovanna Carreira Marinho, Wilson E. Marcílio-Jr, Maurício Araújo Dias, Danilo Medeiros Eler, Almir Olivette Artero, Wallace Correa de Oliveira Casaca, Rogério Galante Negri · 2023 · Remote Sensing
  71. A Fast Search Method for Edge Hazardous Scenarios Based on Semi-Supervised Anomaly Detection
    Mengyu Li, Fang Li, Zihan Guo, Lifang Wang · 2023 · SAE technical papers on CD-ROM/SAE technical paper series
  72. Control of an Electrical System by Recurrent Neural Network RSOM map
    Néjib Khalfaoui, Mohamed Salah Salhi, Tahar Bahi · 2023 · International Multi-Conference on Systems, Signals & Devices (SSD)
  73. A Study on Gait Quality Assessment for Cerebral Palsy Using Unsupervised Deep Learning Model
    Ginga SUMI, Takumi KITAJIMA, Hiroharu Kawanaka, Balaji Iyer, V. B. Surya Prasath, Bruce J. Aronow · 2024 · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
  74. Anomaly detection method combining sample subspace distribution and generative models
    Mengyang Shen, Wanghu Chen, Jing Li · 2023 · International Conference on Algorithms, Computing and Artificial Intelligence (ACAI)
  75. A modified reweighted fast consistent and high-breakdown estimator for high-dimensional datasets
    Ishaq Abdullahi Baba, Habshah Midi, Leong W. June, Gafurjan Ismailovich Ibragimov · 2024 · Decision Analytics Journal
  76. Outlier for High Dimensional Data A Review
    Wasan Abd Majeed, Murtadha Mohammed Hamad · 2023 · International Conference on Developments in eSystems Engineering (DeSE)
  77. Identification of horizontal gene transference by means of anomaly detection and natural language-inspired interpretable embeddings
    Víctor Lomas-Barrié, Michelle Reyes-Camacho, Antonio Neme · 2024 · Journal of Intelligent & Fuzzy Systems
  78. Anomalous Node Detection in a Graph Considering Text Features
    Yeonju Song, Ki Yong Lee · 2024 · Studies in computational intelligence
  79. The Solar System Notification Alert Processing System (SNAPS): Asteroid Population Outlier Detection
    Michael Gowanlock, David E. Trilling, Daniel Kramer, Maria Chernyavskaya, Andrew McNeill · 2024 · The Astronomical Journal
  80. A survey on outlier detection methods in data mining
    Roy Thomas, J. E. Judith · 2019 · International Journal of Engineering & Technology
  81. Tensor-Based Approach to Diagnostic Causal Network Modeling
    Claudiu Radu Pozna, Radu‐Emil Precup, Áron Ballagi · 2024 · Topics in intelligent engineering and informatics
  82. Towards Full Population Testing in Auditing: How Many Process Deviations Should Be Labeled?
    Manal Laghmouch, Benoît Depaire, Mieke Julie Jans · 2024 · International Conference on Process Mining (ICPM)
  83. Memory Residual Regression Autoencoder for Bearing Fault Detection
    Guangrui Wen, Zihao Lei, Xuefeng Chen, Xin Huang · 2024 · Smart sensors, measurement and instrumentation
  84. TMemAE: Handwriting Abnormality Analysis for Parkinson Disease
    Jing Chen, Yuming Fu, Huafeng Qin, Qun Song, Yong Zhou, Simon James Fong · 2024 · International Conference on Big Data and Internet of Things (BDIOT)
  85. Vehicle Network Intrusion Detection Based on K-nearest Neighbor Variational Autoencoder Using Contrastive Learning
    Chenyun Duan, Lei Du, Liyi Zeng, Zhaoquan Gu · 2024 · IEEE International Conference on Data Science in Cyberspace
  86. Multi-Space Tree with Incremental Construction for GPU-Accelerated Range Queries
    Brian Donnelly, Michael Gowanlock · 2024 · IEEE International Conference on High Performance Computing, Data, and Analytics
  87. Multi-target Penetration Path Planning for UAV Swarms Based on Time Synchronization Constraints
    Jiusong Feng, Liyuan Fan, Jinwen Hu, Zhao Xu, Junwei Han · 2025 · Lecture notes in electrical engineering
  88. Enhanced Pruning Process with DBSCAN for Attack Detection
    Gian Maxmillian Firdaus, Vera Suryani · 2024 · International Conference on Cyber Security and Computing (CyberComp)
  89. WarpDrive: Boosting Auto Loan Default Data Processing with GAN-Powered Data Augmentation and SAE-Based Rectification
    Zhu Xueping, Qin Lin, Suzani Mohamad Samuri, Muhamad Hariz Muhamad Adnan · 2025 · Asia-Europe Conference on Cybersecurity, Internet of Things and Soft Computing (CITSC)
  90. Assessment of patient waiting time and queue length using simulation model and machine learning techniques
    Jagriti Gupta, Naresh Sharma · 2025 · Research Square
  91. Unsupervised Detection of Anomaly in Public Procurement Processes
    Jose Pablo Arroyo-Castro, Shu Wei Chou-Chen · 2025 · Studies in classification, data analysis, and knowledge organization
  92. Adversarial Anomaly Explanation
    Fabrizio Angiulli, Fabio Fassetti, Simona Nisticò, Luigi Palopoli · 2025 · Information Systems Frontiers
  93. Exploiting Machine Learning and Remote Sensing for Precision Crop Mapping in Africa
    Omar Ayman, Mosaab Emad Gamal, Mohamed ElSayed Atwa, Yassin Khaled, Noha Gamal El-Din Saad · 2024 · International Conference on Computer Theory and Applications (ICCTA)
  94. Enhanced Stratified Sampling-Density-Based Spatial Clustering of Applications With Noise (SS-DBSCAN) for High-Dimensional Data
    Gloriana Joseph Monko, Masaomi Kimura · 2025 · Data Science
  95. LEVERAGING AI AND BLOCKCHAIN FOR DECENTRALIZED CREDENTIAL VERIFICATION: A CASE STUDY IN ZIMBABWE’S EDUCATION SECTOR
    Roy Kanavheti, Wellington Makondo, Wellington Simbarashe Manjoro · 2025 · International Journal of Computer Science and Mobile Computing
  96. Mitigating Error Propagation in Generative AI via Dimensionality Modulation as a Method for Safe Biomedical Dataset Augmentation
    Jörn Lötsch, Dario Kringel · 2025 · SSRN Electronic Journal
  97. Random Projection-based Anomaly Detection (RPAD) Algorithm
    Ossama Cherkaoui, Houda Anoun, Abderrahim Maizate · 2025 · International Journal of Information Technology & Decision Making
  98. QINN-Based Approach to Detect Anomalies in High-Dimensional Secure Data
    V. Thamilarasi, Nitendra Kumar, P. Ganeshkumar, G. Sivaraman, R. RajiniGanth, Janaki Sivakumar · 2025 · IGI Global eBooks
  99. SL-DSVDD: Scale learning based deep support vector data description network for EV battery anomaly detection
    Chuanjie Liao, Dandan Peng, Jinpeng Tian, Zisheng Wang, Chenyu Liu · 2025 · Journal of Energy Storage
  100. Toward Automated Anomaly Detection and Categorization in Polymer Fiber Production
    Aref Sayareh, Vimal Simha, Joshua Swamidas, Thiago Eustaquio Alves de Oliveira, Amílcar Soares, Vinicius Prado da Fonseca · 2025 · IEEE International Symposium on Industrial Electronics (ISIE)