Efficient SVDD sampling with approximation guarantees for the decision boundary

DOI10.1007/s10994-022-06149-0OpenAlexW3091249049MaRDI QIDQ2163193

Daniel Kottke, Holger Trittenbach, Adrian Englhardt, Bernhard Sick, Klemens Böhm

Publication date: 10 August 2022

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.13853

zbMATH Keywords

data reductionoutlier detectionone-class classificationanomaly detection

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• Julia

Cites Work

• Unnamed Item
• Support vector data description
• Estimating the Support of a High-Dimensional Distribution
• Outlier Analysis
• Julia: A Fresh Approach to Numerical Computing
• 10.1162/15324430260185619
• Data Mining
• Multivariate Density Estimation

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