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 201–210 of 703 papers

Title	Date	Tasks	Status	Hype
RODD: Robust Outlier Detection in Data Cubes	Mar 14, 2023	Outlier Detection	—Unverified	0
Interpretable Outlier Summarization	Mar 11, 2023	Anomaly DetectionOutlier Detection	—Unverified	0
AnoMalNet: Outlier Detection based Malaria Cell Image Classification Method Leveraging Deep Autoencoder	Mar 10, 2023	image-classificationImage Classification	—Unverified	0
Image Labels Are All You Need for Coarse Seagrass Segmentation	Mar 2, 2023	AllOutlier Detection	CodeCode Available	0
Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain	Feb 27, 2023	Contribution AssessmentFederated Learning	—Unverified	0
Cluster Purging: Efficient Outlier Detection based on Rate-Distortion Theory	Feb 22, 2023	ClusteringData Compression	—Unverified	0
ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment	Feb 20, 2023	Federated LearningOutlier Detection	—Unverified	0
SplitOut: Out-of-the-Box Training-Hijacking Detection in Split Learning via Outlier Detection	Feb 16, 2023	Outlier Detection	CodeCode Available	1
Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics	Feb 13, 2023	Anomaly DetectionOne-Class Classification	—Unverified	0
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis	Feb 11, 2023	Image-text RetrievalKnowledge Graphs	CodeCode Available	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