27 citations · 62 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…
The Mean and Median Criterion for Automatic Kernel Bandwidth Selection for Support Vector Data Description
Arin Chaudhuri, Deovrat Kakde, Carol Sadek +2
Support vector data description (SVDD) is a popular technique for detecting anomalies. The SVDD classifier partitions the whole space into an inlier region, which consists of the r…
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…