Background: Mathematical modeling is being applied to increasingly complex biological systems and datasets; however, the process of analyzing and calibrating against experimental ...
Kyoung Ae Kim, Sabrina L. Spencer, John G. Albeck,...
Statistical data is present everywhere—from governmental bodies to economics, from life-science to industry. With the rise of the Web of Data, the need for sharing, accessing, an...
Michael Hausenblas, Wolfgang Halb, Yves Raimond, L...
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
Production grids are complex and highly variable systems whose behavior is not well understood and difficult to anticipate. The goal of this study is to estimate the impact of the ...
Networks are becoming a unifying framework for modeling complex systems and network inference problems are frequently encountered in many fields. Here, I develop and apply a gener...