Decision Trees are well known for their training efficiency and their interpretable knowledge representation. They apply a greedy search and a divide-and-conquer approach to learn...
Mingyu Zhong, Michael Georgiopoulos, Georgios C. A...
Consider a supervised learning problem in which examples contain both numerical- and text-valued features. To use traditional featurevector-based learning methods, one could treat...
Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, ...
The Constraint Satisfaction Problem (CSP) framework allows users to define problems in a declarative way, quite independently from the solving process. However, when the problem i...
Jean-Marie Normand, Alexandre Goldsztejn, Marc Chr...
Abstract. The Semantic Web is an effort by the W3C to enable integration and sharing of information across different applications and organizations using annotations by means of on...
Abstract. This paper presents parallel approaches to the complete transient numerical analysis of stochastic reward nets (SRNs) for both shared and distributed-memory machines. Par...