Model selection is an important ingredient of many machine learning algorithms, in particular when the sample size in small, in order to strike the right trade-off between overfitt...
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Background: Evolutionary analysis provides a formal framework for comparative analysis of genomic and other data. In evolutionary analysis, observed data are treated as the termin...
Thomas Hladish, Vivek Gopalan, Chengzhi Liang, Wei...
Texture has been recognized as an important visual primitive in image analysis. A widely used texture descriptor, which is part of the MPEG-7 standard, is that computed using mult...