Abstract— Motivated by applications in cryptography, we consider a generalization of randomness extraction and the related notion of privacy amplification to the case of two cor...
We study the problem of automatically discovering semantic associations between schema elements, namely foreign keys. This problem is important in all applications where data sets...
Alexandra Rostin, Oliver Albrecht, Jana Bauckmann,...
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
The ranking problem appears in many areas of study such as customer rating, social science, economics, and information retrieval. Ranking can be formulated as a classification pro...