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 421–430 of 703 papers

Title	Date	Tasks	Status	Hype
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video	Aug 27, 2020	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1
Let me join you! Real-time F-formation recognition by a socially aware robot	Aug 23, 2020	Outlier Detection	—Unverified	0
A boosted outlier detection method based on the spectrum of the Laplacian matrix of a graph	Aug 7, 2020	ClusteringOutlier Detection	—Unverified	0
Outlier detection in non-elliptical data by kernel MRCD	Aug 5, 2020	Outlier Detection	CodeCode Available	0
Rotational Outlier Identification in Pose Graphs Using Dual Decomposition	Aug 1, 2020	Outlier DetectionSimultaneous Localization and Mapping	—Unverified	0
ALRe: Outlier Detection for Guided Refinement	Aug 1, 2020	Outlier Detection	—Unverified	0
Handcrafted Outlier Detection Revisited	Aug 1, 2020	Outlier DetectionVisual Localization	CodeCode Available	1
Byzantine-Resilient Secure Federated Learning	Jul 21, 2020	Federated LearningOutlier Detection	—Unverified	0
Integrating Network Embedding and Community Outlier Detection via Multiclass Graph Description	Jul 20, 2020	Community DetectionGraph Embedding	CodeCode Available	0
Data Stream Clustering: A Review	Jul 16, 2020	ClusteringOutlier Detection	—Unverified	0

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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