Outlier Detection

Outlier Detection is a task of identifying a subset of a given data set which are considered anomalous in that they are unusual from other instances. It is one of the core data mining tasks and is central to many applications. In the security field, it can be used to identify potentially threatening users, in the manufacturing field it can be used to identify parts that are likely to fail.

Source: Coverage-based Outlier Explanation

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 371–380 of 703 papers

Title	Date	Tasks	Status
Rectifying Self Organizing Maps for Automatic Concept Learning from Web Images	Dec 16, 2013	ClusteringImage Retrieval	—Unverified
Re-experiment Smart: a Novel Method to Enhance Data-driven Prediction of Mechanical Properties of Epoxy Polymers	May 19, 2025	Outlier Detection	—Unverified
Regularized Contrastive Partial Multi-view Outlier Detection	Aug 2, 2024	AttributeContrastive Learning	—Unverified
Relative Density-Ratio Estimation for Robust Distribution Comparison	Dec 1, 2011	Density Ratio EstimationOutlier Detection	—Unverified
ReLearn: A Robust Machine Learning Framework in Presence of Missing Data for Multimodal Stress Detection from Physiological Signals	Apr 29, 2021	BIG-bench Machine Learningfeature selection	—Unverified
REMIX: Automated Exploration for Interactive Outlier Detection	May 17, 2017	Meta-LearningOutlier Detection	—Unverified
Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection---Extended Version	Apr 7, 2022	Outlier DetectionTime Series	—Unverified
Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy	Nov 16, 2019	Anomaly DetectionBackdoor Attack	—Unverified
Robust Classification by Pre-conditioned LASSO and Transductive Diffusion Component Analysis	Nov 19, 2015	BIG-bench Machine LearningClassification	—Unverified
Robust Contextual Outlier Detection: Where Context Meets Sparsity	Jul 28, 2016	Outlier Detection	—Unverified

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All datasets ECG5000 Balance scale_class 1 Breast cancer Wisconsin_class 2 Breast cancer Wisconsin_class 4 Fashion-MNIST Glass identification Heart-C Hepatitis Internet Ad Ionosphere_class b SKAB

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	VRAE+SVM	Accuracy	0.98	—	Unverified
2	F-t ALSTM-FCN	Accuracy	0.95	—	Unverified
3	GENDIS	Accuracy	0.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	99.03	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	37.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	65.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PAE	AUROC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	99.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC	0.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC-ROC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIX	AUC-ROC	0.93	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ASVDD	Average Accuracy	86.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSTMCaps	Average F1	0.74	—	Unverified