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 411–420 of 703 papers

Title	Date	Tasks	Status
ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg"	Feb 10, 2019	BenchmarkingClustering	—Unverified
Enabling Efficient Privacy-Assured Outlier Detection over Encrypted Incremental Datasets	Nov 14, 2019	Anomaly DetectionOutlier Detection	—Unverified
Enhancement to Training of Bidirectional GAN : An Approach to Demystify Tax Fraud	Aug 16, 2022	Outlier Detection	—Unverified
Enhancing Intrusion Detection In Internet Of Vehicles Through Federated Learning	Nov 23, 2023	Federated LearningIntrusion Detection	—Unverified
Enhancing Sentiment Analysis Results through Outlier Detection Optimization	Nov 25, 2023	Language ModelingLanguage Modelling	—Unverified
Enhancing Visual Representations for Efficient Object Recognition during Online Distillation	Jan 1, 2021	Object RecognitionOutlier Detection	—Unverified
Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies	Mar 31, 2025	Data AugmentationDomain Adaptation	—Unverified
Exact Subspace Segmentation and Outlier Detection by Low-Rank Representation	Sep 8, 2011	Outlier Detection	—Unverified
Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networks	Jan 23, 2025	Beam PredictionOutlier Detection	—Unverified
Exploring Information Centrality for Intrusion Detection in Large Networks	Apr 27, 2019	Anomaly DetectionIntrusion 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