Deciding what to branch on at each node is a key element of search algorithms. We present four families of methods for selecting what question to branch on. They are all informati...
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
This article gives an overview of a framework for automatically generating large-scale simulation models from a domain specific problem definition data schema, here semiconductor ...
Ralph Mueller, Christos Alexopoulos, Leon F. McGin...
We study the problem of learning large margin halfspaces in various settings using coresets to show that coresets are a widely applicable tool for large margin learning. A large m...
Many interesting problems, including Bayesian network structure-search, can be cast in terms of finding the optimum value of a function over the space of graphs. However, this fun...