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 581–590 of 703 papers

Title	Date	Tasks	Status
Implications of Distance over Redistricting Maps: Central and Outlier Maps	Mar 2, 2022	FairnessOutlier Detection	—Unverified
Characterizing Malicious Edges targeting on Graph Neural Networks	Sep 27, 2018	Graph GenerationLink Prediction	—Unverified
Choquet-Based Fuzzy Rough Sets	Feb 22, 2022	BIG-bench Machine LearningOutlier Detection	—Unverified
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model	Jan 20, 2025	Anomaly DetectionOutlier Detection	—Unverified
Closed-Form, Provable, and Robust PCA via Leverage Statistics and Innovation Search	Jun 23, 2021	ClusteringForm	—Unverified
Clustering with Outlier Removal	Jan 5, 2018	ClusteringOutlier Detection	—Unverified
Cluster Purging: Efficient Outlier Detection based on Rate-Distortion Theory	Feb 22, 2023	ClusteringData Compression	—Unverified
Cognitive Deep Machine Can Train Itself	Dec 2, 2016	Outlier Detection	—Unverified
Combining Structured and Unstructured Randomness in Large Scale PCA	Oct 23, 2013	BIG-bench Machine LearningOutlier Detection	—Unverified
Community-based anomaly detection using spectral graph filtering	Jan 24, 2022	Anomaly DetectionOutlier 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