Learn about the common challenges and limitations of linear and nonlinear programming methods and how to overcome or mitigate them for algorithm design.

Learn what linear and nonlinear models are, how they differ, and how they are applied in neural networks with real-world examples.

The support vector machine (SVM) is one of the most well-known supervised machine learning algorithms. SVM offers a variety of flexible kernel methods to suit different datasets from different fields ...

Asymptotic expansions of the distributions of the linear and the quadratic discriminant functions are derived. The expected misclassification probabilities of these two functions are compared when the ...

In this problem, the optimal path is one that maximizes the expected utility, with the utility function being piecewise-linear and concave. Such a utility function can be used to approximate nonlinear ...

By definition, UAV means Unmanned Aerial Vehicle, which in fact has been growing in the recent years, encouraged by technological developments, especially in the electronics and military automation ...