“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
Recent work has demonstrated the effectiveness of the wavelet decomposition in reducing large amounts of data to compact sets of wavelet coefficients (termed "wavelet synopse...
A fast algorithm, Accelerated Kernel Feature Analysis (AKFA), that discovers salient features evidenced in a sample of n unclassified patterns, is presented. Like earlier kernel-b...
Xianhua Jiang, Yuichi Motai, Robert R. Snapp, Xing...
We introduce a method to discover optimal local patterns, which concisely describe the main trends in a time series. Our approach examines the time series at multiple time scales ...
Abstract: We propose a hyperspectral image compressor called BH which considers its input image as being partitioned into square blocks, each lying entirely within a particular ban...