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One of the most common problems in machine learning and statistics consists of estimating the mean response X.beta from a vector of observations y assuming y=X.beta+epsilon where X is known, beta is a vector of parameters of interest and epsilon a vector of stochastic errors. We are particularly int ...

We develop a novel Bayesian nonparametric model for random bipartite graphs. The model is based on the theory of completely random measures and is able to handle a potentially infinite number of nodes. We show that the model has appealing properties and in particular it may exhibit a power-law behav ...