In this work we consider an inference task that biologists are very good at: deciphering biological processes by bringing together knowledge that has been obtained by experiments u...
Christian Widmer, Jose Leiva, Yasemin Altun, Gunna...
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
In this paper, active learning with support vector machines (SVMs) is applied to the problem of tornado prediction. This method is used to predict which storm-scale circulations yi...
Theodore B. Trafalis, Indra Adrianto, Michael B. R...
Abstract. The paper presents an algorithm for identifying the independent subspace analysis model based on source dynamics. We propose to separate subspaces by decoupling their dyn...
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...