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 261–270 of 703 papers

Title	Date	Tasks	Status
Cluster Purging: Efficient Outlier Detection based on Rate-Distortion Theory	Feb 22, 2023	ClusteringData Compression	—Unverified
ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment	Feb 20, 2023	Federated LearningOutlier Detection	—Unverified
Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics	Feb 13, 2023	Anomaly DetectionOne-Class Classification	—Unverified
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis	Feb 11, 2023	Image-text RetrievalKnowledge Graphs	CodeCode Available
Real-Time Outlier Detection with Dynamic Process Limits	Jan 31, 2023	Anomaly DetectionOutlier Detection	—Unverified
Conformal inference is (almost) free for neural networks trained with early stopping	Jan 27, 2023	Multi-class ClassificationOutlier Detection	CodeCode Available
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models	Jan 11, 2023	MemorizationOutlier Detection	CodeCode Available
A Meta-Learning Algorithm for Interrogative Agendas	Jan 4, 2023	Meta-LearningOutlier Detection	—Unverified
EDoG: Adversarial Edge Detection For Graph Neural Networks	Dec 27, 2022	Drug DesignEdge Detection	—Unverified
LOSDD: Leave-Out Support Vector Data Description for Outlier Detection	Dec 27, 2022	One-Class ClassificationOutlier 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