We give results about the learnability and required complexity of logical formulae to solve classification problems. These results are obtained by linking propositional logic with...
Adam Kowalczyk, Alex J. Smola, Robert C. Williamso...
When constructing a classifier, the probability of correct classification of future data points should be maximized. In the current paper this desideratum is translated in a very ...
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib...
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the ...
Abstract. Computing a maximum weighted stable set in a bipartite graph is considered wellsolved and usually approached with preflow-push, Ford-Fulkerson or network simplex algorith...