A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
The success of UML and more generally, of the model driven approach, has led to a proliferation of models, representing various systems, but the description of large applications ...
Given a query image of an object, our objective is to retrieve all instances of that object in a large (1M+) image database. We adopt the bag-of-visual-words architecture which ha...
Ondrej Chum, James Philbin, Josef Sivic, Michael I...
This paper presents an approach for building consensus ontologies from the individual ontologies of a network of socially interacting agents. Each agent has its own conceptualizat...