In this paper, we present a simple method for generating random-based signatures when random number generators are either unavailable or of suspected quality (malicious or accident...
Slope selection is a well-known algorithmic tool used in the context of computing robust estimators for fitting a line to a collection P of n points in the plane. We demonstrate th...
Random sampling is a well-known technique for approximate processing of large datasets. We introduce a set of algorithms for incremental maintenance of large random samples on seco...
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
Abstract—We consider the problem of jointly optimizing random access and subgraph selection in coded wireless packet networks. As opposed to the corresponding scheduling approach...
Maximilian Riemensberger, Michael Heindlmaier, And...