Dimension reduction techniques have been successfully applied to face recognition and text information retrieval. The process can be time-consuming when the data set is large. Thi...
Dimensionality reduction (DR) is a major issue to improve the efficiency of the classifiers in Hyperspectral images (HSI). Recently, the independent component analysis (ICA) app...
Hash functions play the most important role in various cryptologic applications, ranging from data integrity checking to digital signatures. Our goal is to introduce a new hash fu...
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...