Giacomo Zanella — accepted AI-conference papers

2024

Robust Approximate Sampling via Stochastic Gradient Barker Dynamics

AISTATS 2024poster

Stochastic Gradient (SG) Markov Chain Monte Carlo algorithms (MCMC) are popular algorithms for Bayesian sampling in the presence of large datasets. However, they come with little theoretical guarantees and assessing their empirical performances is non-trivial. In such context, it is crucial to devel…

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2016

Flexible Models for Microclustering with Application to Entity Resolution

Brenda Betancourt, Giacomo Zanella, Jeffrey W Miller, Hanna Wallach, Abbas Zaidi, Rebecca C. Steorts

NeurIPS 2016poster

Most generative models for clustering implicitly assume that the number of data points in each cluster grows linearly with the total number of data points. Finite mixture models, Dirichlet process mixture models, and Pitman--Yor process mixture models make this assumption, as do all other infinitely…

Cited by 60 Source ↗PDF ↗Scholar ↗