The main purpose of this paper is to promote the study of computational aspects, primarily the convergence rate, of nonlinear dynamical systems from a combinatorial perspective. W...
Machine learning techniques such as tree induction have become accepted tools for developing generalisations of large data sets, typically for use with production rule systems in p...
With increasing complexity of modern embedded systems, the availability of highly optimizing compilers becomes more and more important. At the same time, application specific inst...
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
Abstract. We introduce approximate data exchange, by relaxing classical data exchange problems such as Consistency and Typechecking to their approximate versions based on Property ...