SOTAVerified

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

Showing 601625 of 703 papers

TitleStatusHype
Scalable Support Vector Clustering Using Budget0
LSTM Fully Convolutional Networks for Time Series ClassificationCode1
Zipporah: a Fast and Scalable Data Cleaning System for Noisy Web-Crawled Parallel Corpora0
Identifying Semantically Deviating Outlier Documents0
Fast Incremental SVDD Learning Algorithm with the Gaussian KernelCode0
Visualizing and Exploring Dynamic High-Dimensional Datasets with LION-tSNE0
Detection of Abnormal Input-Output Associations0
Anomaly Detection by Robust Statistics0
KNN Ensembles for Tweedie Regression: The Power of Multiscale Neighborhoods0
Exploring Outliers in Crowdsourced Ranking for QoE0
Learning Geometric Concepts with Nasty Noise0
Outlier-Robust Tensor PCA0
Pay Attention to the Ending:Strong Neural Baselines for the ROC Story Cloze Task0
ECO-AMLP: A Decision Support System using an Enhanced Class Outlier with Automatic Multilayer Perceptron for Diabetes Prediction0
A Robust Learning Algorithm for Regression Models Using Distributionally Robust Optimization under the Wasserstein Metric0
The Geometry of Nodal Sets and Outlier Detection0
Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization0
REMIX: Automated Exploration for Interactive Outlier Detection0
Provable Self-Representation Based Outlier Detection in a Union of Subspaces0
Word Embeddings via Tensor FactorizationCode0
Efficient variational Bayesian neural network ensembles for outlier detectionCode0
Deep SetsCode1
Outlier Cluster Formation in Spectral Clustering0
Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation0
Outlier Detection for Text Data : An Extended VersionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VRAE+SVMAccuracy0.98Unverified
2F-t ALSTM-FCNAccuracy0.95Unverified
3GENDISAccuracy0.94Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.03Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy37.62Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy65.6Unverified
#ModelMetricClaimedVerifiedStatus
1PAEAUROC1Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.05Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC0.86Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.85Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.93Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy86.33Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMCapsAverage F10.74Unverified