A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
To solve real-world discrete optimization problems approximately metaheuristics such as simulated annealing and other local search methods are commonly used. For large instances o...
This paper presents the Real-coded Genetic Algorithms for high-dimensional ill-scaled structures, what is called, the ktablet structure. The k-tablet structure is the landscape th...
The most popular approaches for the simulation of dynamic systems in computer graphics are force based. Internal and external forces are accumulated from which accelerations are c...
This paper addresses the issues of nonlinear edge-preserving image smoothing and segmentation. A ML-based approach is proposed which uses an iterative algorithm to solve the probl...