16 citations · 50 across the 5 of their papers we have counts for
5 papers
The Trace Criterion for Kernel Bandwidth Selection for Support Vector Data Description
Arin Chaudhuri, Carol Sadek, Deovrat Kakde +6
Support vector data description (SVDD) is a popular anomaly detection technique. The SVDD classifier partitions the whole data space into an inlier region, which consists of the re…
A new bandwidth selection criterion for using SVDD to analyze hyperspectral data
Yuwei Liao, Deovrat Kakde, Arin Chaudhuri +3
This paper presents a method for hyperspectral image classification that uses support vector data description (SVDD) with the Gaussian kernel function. SVDD has been a popular mach…
Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel
Hansi Jiang, Haoyu Wang, Wenhao Hu +2
Support vector data description (SVDD) is a machine learning technique that is used for single-class classification and outlier detection. The idea of SVDD is to find a set of supp…
Sampling Method for Fast Training of Support Vector Data Description
Arin Chaudhuri, Deovrat Kakde, Maria Jahja +4
Support Vector Data Description (SVDD) is a popular outlier detection technique which constructs a flexible description of the input data. SVDD computation time is high for large t…
Peak Criterion for Choosing Gaussian Kernel Bandwidth in Support Vector Data Description
Deovrat Kakde, Arin Chaudhuri, Seunghyun Kong +3
Support Vector Data Description (SVDD) is a machine-learning technique used for single class classification and outlier detection. SVDD formulation with kernel function provides a…