The routing in communication networks is typically a multicriteria decision making (MCDM) problem. However, setting the parameters of most used MCDM methods to fit the preferences ...
We introduce novel results for approximate inference on planar graphical models using the loop calculus framework. The loop calculus (Chertkov and Chernyak, 2006b) allows to expre...
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...
In this study, we combined the ChIP-seq and the transcriptome data and integrated these data into signaling cascades. Integration was realized through a framework based on data- a...