Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
The present paper deals with the learnability of indexed families of uniformly recursive languages from positive data as well as from both, positive and negative data. We consider...
Reproducing and learning from failures in deployed software is costly and difficult. Those activities can be facilitated, however, if the circumstances leading to a failure are p...
Sebastian G. Elbaum, Satya Kanduri, Anneliese Amsc...
We present a technique for automatic induction of slot annotations for subcategorization frames, based on induction of hidden classes in the EM framework of statistical estimation...
Mats Rooth, Stefan Riezler, Detlef Prescher, Glenn...
Abstract. Anyone offering content in a digital library is naturally interested in assessing its performance: how well does my system meet the users' information needs? Standar...