= Giacomo Zanella
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<Giacomo Zanella> develops methods in <computational statistics>, applied <probability theory> and <machine learning>, especially Bayesian computation. His research statement identifies <Markov chain Monte Carlo>, random measures and variable selection among these interests.https://sites.google.com/site/gzanellawebpage/home[Author research statement]{ref}
With <Gareth Roberts>, he proposed the <Tempered Gibbs sampler>. A modified coordinate-selection rule can explore difficult high-dimensional targets more effectively; <importance sampling> weights then recover averages under the desired <probability distribution>. Their analysis includes applications to Bayesian variable selection.<Scalable Importance Tempering and Bayesian Variable Selection by Giacomo Zanella and Gareth Roberts>[Abstract and section 2]{ref}
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