Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...
We present an efficient method for maximizing energy functions with first and second order potentials, suitable for MAP labeling estimation problems that arise in undirected graph...
When monitoring spatial phenomena, which are often modeled as Gaussian Processes (GPs), choosing sensor locations is a fundamental task. A common strategy is to place sensors at t...
We present in this paper a combination of Machine Learning based Information Retrieval (IR) techniques and stochastic language modelling in a hierarchical system that extracts sur...