Dependent normalized random measures
Bayesian nonparametrics, since its introduction, has gained increasing attention in machine learning due to its flexibility in modeling. Essentially, Bayesian nonparametrics defines distributions over infinite dimensional objects such as discrete distributions and smooth functions. This overcomes the fundamental problem of model selection which is hard in traditional machine learning, thus is appealing in both application and theory. Among the Bayesian nonparametric family, random probability...[Show more]
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