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

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Showing 301–350 of 703 papers

TitleStatusHype
Learning Geometric Concepts with Nasty Noise—0
GAN-RXA: A Practical Scalable Solution to Receiver-Agnostic Transmitter Fingerprinting—0
C-AllOut: Catching & Calling Outliers by Type—0
Closed-Form, Provable, and Robust PCA via Leverage Statistics and Innovation Search—0
Anomaly Detection for Unmanned Aerial Vehicle Sensor Data Using a Stacked Recurrent Autoencoder Method with Dynamic Thresholding—0
ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment—0
Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networks—0
Generating Artificial Outliers in the Absence of Genuine Ones -- a Survey—0
Generative Models for Novelty Detection: Applications in abnormal event and situational change detection from data series—0
Clustering with Outlier Removal—0
Byzantine-Resilient Secure Federated Learning—0
Geometric Tight Frame based Stylometry for Art Authentication of van Gogh Paintings—0
Cluster Purging: Efficient Outlier Detection based on Rate-Distortion Theory—0
A boosted outlier detection method based on the spectrum of the Laplacian matrix of a graph—0
Graph-Embedded Multi-layer Kernel Extreme Learning Machine for One-class Classification or (Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification)—0
GraphPrints: Towards a Graph Analytic Method for Network Anomaly Detection—0
GWQ: Gradient-Aware Weight Quantization for Large Language Models—0
HAITCH: A Framework for Distortion and Motion Correction in Fetal Multi-Shell Diffusion-Weighted MRI—0
A Bayesian Ensemble for Unsupervised Anomaly Detection—0
Hardware Architecture Proposal for TEDA algorithm to Data Streaming Anomaly Detection—0
Hierarchical Multiresolution Feature- and Prior-based Graphs for Classification—0
Highly Efficient Direct Analytics on Semantic-aware Time Series Data Compression—0
HLoOP -- Hyperbolic 2-space Local Outlier Probabilities—0
Holistic Features For Real-Time Crowd Behaviour Anomaly Detection—0
Homophily Outlier Detection in Non-IID Categorical Data—0
Evaluating the Efficacy of Foundational Models: Advancing Benchmarking Practices to Enhance Fine-Tuning Decision-Making—0
Hybridization of Capsule and LSTM Networks for unsupervised anomaly detection on multivariate data—0
Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles—0
Hyperbolic Metric Learning for Visual Outlier Detection—0
Capturing the Denoising Effect of PCA via Compression Ratio—0
K-NS: Section-Based Outlier Detection in High Dimensional Space—0
Identifying Informative Latent Variables Learned by GIN via Mutual Information—0
Identifying Outlier Arms in Multi-Armed Bandit—0
Identifying Semantically Deviating Outlier Documents—0
Exact Subspace Segmentation and Outlier Detection by Low-Rank Representation—0
Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies—0
Image Modeling with Deep Convolutional Gaussian Mixture Models—0
Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation—0
Impacts of the Numbers of Colors and Shapes on Outlier Detection: from Automated to User Evaluation—0
Conditional Testing based on Localized Conformal p-values—0
Breakdown Point of Robust Support Vector Machine—0
Improving Solar Flare Prediction by Time Series Outlier Detection—0
Improving the Robustness of Federated Learning for Severely Imbalanced Datasets—0
Incremental Outlier Detection Modelling Using Streaming Analytics in Finance & Health Care—0
Anomaly Detection for an E-commerce Pricing System—0
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach—0
Brain Ageing Prediction using Isolation Forest Technique and Residual Neural Network (ResNet)—0
Irregularity Detection in Categorized Document Corpora—0
It Is Likely That Your Loss Should be a Likelihood—0
Enhancing Visual Representations for Efficient Object Recognition during Online Distillation—0
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All datasetsECG5000Balance scale_class 1Breast cancer Wisconsin_class 2Breast cancer Wisconsin_class 4Fashion-MNISTGlass identificationHeart-CHepatitisInternet AdIonosphere_class bSKAB

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VRAE+SVMAccuracy0.98—Unverified
2F-t ALSTM-FCNAccuracy0.95—Unverified
3GENDISAccuracy0.94—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.03—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy37.62—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy65.6—Unverified
#ModelMetricClaimedVerifiedStatus
1PAEAUROC1—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy99.05—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1MIXAUC-ROC0.93—Unverified
#ModelMetricClaimedVerifiedStatus
1ASVDDAverage Accuracy86.33—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMCapsAverage F10.74—Unverified