Abstract. A new method is proposed for compiling causal independencies into Markov logic networks (MLNs). An MLN can be viewed as compactly representing a factorization of a joint ...
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasa...
Current knowledge bases suffer from either low coverage or low accuracy. The underlying hypothesis of this work is that user feedback can greatly improve the quality of automatica...
Gjergji Kasneci, Jurgen Van Gael, Ralf Herbrich, T...
Abstract. One of the key problems in model-based reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large relational domains, in wh...
In this paper, we consider the problem of community detection in directed networks by using probabilistic models. Most existing probabilistic models for community detection are ei...
The efficient similarity search in metric spaces is usually based on several low-level partitioning principles, which allow filtering of non-relevant objects during the search. I...