Although algorithms that employ dynamic reconfiguration are extremely fast, they need the underlying architecture to change structure very rapidly, possibly at each step of the c...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Abstract. Researchers have focused on assessing the quality of search algorithms by measuring effort, number of mistakes, runtime distributions and other characteristics. In this p...
This paper describes an automatic annotation, or autotagging, algorithm that attaches textual tags to 3D models based on their shape and semantic classes. The proposed method emplo...
In this paper, we present the index-permutation (IP) graph model, and apply it to the systematic development of efficient hierarchical networks. We derive several classes of inter...