We consider an active learning game within a transductive learning model. A major problem with many active learning algorithms is that an unreliable current hypothesis can mislead...
Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions. It has been shown that GP can bene ...
In this paper we propose a new distributed learning method called distributed network boosting (DNB) algorithm for distributed applications. The learned hypotheses are exchanged b...
Machine learning and statistical methods have yielded impressive results in a wide variety of natural language processing tasks. These advances have generally been regarded as eng...
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...