Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual fo...
Local genetic algorithms have been designed with the aim of providing effective intensification. One of their most outstanding features is that they may help classical local searc...
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
The quadratic linear ordering problem naturally generalizes various optimization problems, such as bipartite crossing minimization or the betweenness problem, which includes linear...
—The article describes a course on system design (structural approach) which involves the following: issues of systems engineering; structural models; basic technological problem...