Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...
A generic architecture for evolutive supervision of robotized assembly tasks is presented. This architecture , at different levels of abstraction, functions for dispatching action...
Due to the large variation and richness of visual inputs, statistical learning gets more and more concerned in the practice of visual processing such as visual tracking and recogn...
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...