We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Content–based image retrieval in the medical domain is an extremely hot topic in medical imaging as it promises to help better managing the large amount of medical images being ...
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
The recent movement by major Web services towards making many application programming interfaces (APIs) available for public use has led to the development of the new MashUp techno...
Andreas Auinger, Martin Ebner, Dietmar Nedbal, And...
Information extraction (IE) holds the promise of generating a large-scale knowledge base from the Web’s natural language text. Knowledge-based weak supervision, using structured...
Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke S....