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We'll use hierarchical modeling to build structured objects that are reminiscent of graphical models—but are nonparametric! – statistical justification—the ...
Combinatorial Stochastic Processes and Nonparametric. Bayesian Modeling. Michael I. Jordan, University of California at Berkeley. Abstract. Computer Science has ...
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Duration: 57:58
Posted: Aug 22, 2014
Posted: Aug 22, 2014
I will give some examples of how this blend of ideas leads to useful models in some applied problem domains, including natural language parsing, computational ...
Dec 18, 2013 · I will give some examples of how this blend of ideas leads to useful models in some applied problem domains, including natural language parsing, ...
Jun 26, 2012 · We review the existing combinatorial stochastic process representations for the clustering problem and develop analogous representations for the ...
Bayesian nonparametric models are a set of interrelated stochastic processes, most notably the Dirichlet process and the Chinese restaurant process. In this ...
▻ Stochastic processes form the core of many Bayesian nonparametric ... Bayesian nonparametric models and stochastic ... Combinatorial stochastic processes.
Combinatorial Stochastic Processes and Nonparametric. Bayesian Modeling. Computer Science has historically been strong on data structures and weak on ...
This is a collection of expository articles about various topics at the interface between enumerative combinatorics and stochastic processes.