This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Web spam detection has become one of the top challenges for the Internet search industry. Instead of using some heuristic rules, we propose a feature re-extraction strategy to opt...
In this paper, we exploit non-local features as an estimate of long-distance dependencies to improve performance on the statistical spoken language understanding (SLU) problem. Th...
Nowadays personal identification is a very important issue. There is a wide range of applications in different spheres, such as video surveillance security systems, control of docu...