Stability is a common tool to verify the validity of sample based algorithms. In clustering it is widely used to tune the parameters of the algorithm, such as the number k of clust...
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...
In order to obtain better generalization performance in supervised learning, model parameters should be determined appropriately, i.e., they should be determined so that the gener...
We consider multivariate density estimation with identically distributed observations. We study a density estimator which is a convex combination of functions in a dictionary and ...