The author presents a rapidly convergent algorithm to solve the general portfolio problem of maximizing concave utility functions subject to linear constraints. The algorithm is based on an iterative ...

One simple illustration is K-nearest neighbor algorithm used for classification. It can be applied to digitizing hand-written characters, detecting hidden packages, etc.