We present an approach to spatial inference which is based on the procedural semantics of spatial relations. In contrast to qualitative reasoning, we do not use discrete symbolic m...
Sylvia Wiebrock, Lars Wittenburg, Ute Schmid, Frit...
A generic architecture for evolutive supervision of robotized assembly tasks is presented. This architecture , at different levels of abstraction, functions for dispatching action...
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vec...
Appropriate feature selection is a very crucial issue in any machine learning framework, specially in Maximum Entropy (ME). In this paper, the selection of appropriate features for...
Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...