Regularized linear classifiers have been successfully applied in undersampled, i.e. small sample size/high dimensionality biomedical classification problems. Additionally, a desig...
We propose practical stopping criteria for the iterative solution of sparse linear least squares (LS) problems. Although we focus our discussion on the algorithm LSQR of Paige and ...
Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the ...
Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Ja...
Gait has received much attention from researchers in the vision field due to its utility in walker identification. One of the key issues in gait recognition is how to extract di...
Using the operational matrix of an orthogonal function to perform integration for solving, identifying and optimizing a linear dynamic system has several advantages: (1) the metho...