SVDD-Based Pattern Denoising

DOI10.1162/neco.2007.19.7.1919zbMath1146.68432OpenAlexW2112323714WikidataQ50996971 ScholiaQ50996971MaRDI QIDQ5457591

Jong-Ho Kim, James T. Kwok, Daesung Kang, Jooyoung Park, Ivor W. Tsang

Publication date: 14 April 2008

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco.2007.19.7.1919

zbMATH Keywords

support vector data description

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items

Noise peeling methods to improve boosting algorithms ⋮ Theoretical analysis for solution of support vector data description ⋮ Dynamic pattern denoising method using multi-basin system with kernels

Cites Work

• Estimating the Support of a High-Dimensional Distribution
• De-noising by soft-thresholding
• Adding a point to vector diagrams in multivariate analysis
• On a connection between kernel PCA and metric multidimensional scaling