The bias-variance decomposition is a very useful and widely-used tool for understanding machine-learning algorithms. It was originally developed for squared loss. In recent years,...
Higher-order tensor decompositions are analogous to the familiar Singular Value Decomposition (SVD), but they transcend the limitations of matrices (second-order tensors). SVD is ...
We present a new intuitive UI, which we call cross-boundary brushes, for interactive mesh decomposition. The user roughly draws one or more strokes across a desired cut and our sy...
In this paper we present an algorithm for converting a BDD representation of a logic function into a multiple-level netlist of disjoint-support subfunctions. On the theoretical si...
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...