Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...
This chapter discusses decision making under uncertainty. More specifically, it offers an overview of efficient Bayesian and distribution-free algorithms for making near-optimal se...
Abstract. A hybrid genetic algorithm is proposed for the sequential ordering problem. It is known that the performance of a genetic algorithm depends on the survival environment an...
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
–- To obtain optimal location area (LA) partitioning in cellular radio networks is important since it maximizes the usable bandwidth to support services. However, we feel that th...
Yong Huat Chew, Boon Sain Yeo, Daniel Chien Ming K...