We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
We present a method for constructing ensembles from libraries of thousands of models. Model libraries are generated using different learning algorithms and parameter settings. For...
Rich Caruana, Alexandru Niculescu-Mizil, Geoff Cre...
Knowledge Management (KM) and E-Learning (EL) applications interface more and more as their objects of concern consist in ’captured knowledge’ resp. ’learning objects’, i....
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...
— This paper is concerned with understanding the connection between the existing Internet congestion control algorithms and the optimal control theory. The available resource all...