We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Recent work on ontology-based Information Extraction (IE) has tried to make use of knowledge from the target ontology in order to improve semantic annotation results. However, ver...
Abstract— Decision trees, being human readable and hierarchically structured, provide a suitable mean to derive state-space abstraction and simplify the inclusion of the availabl...
Masoud Asadpour, Majid Nili Ahmadabadi, Roland Sie...
The work proposes a hierarchical architecture for learning amic scenes at various levels of knowledge abstraction. The raw visual information is processed at different stages to g...
We are interested in learning programs for multiple related tasks given only a few training examples per task. Since the program for a single task is underdetermined by its data, ...