[Forum SIS] Webinar RIGON

[Pierpaolo De Blasi]

WEBINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO
<https://www.carloalberto.org/research/webinars/>


Venerdì 29 Maggio 2020, alle ore 15:00, si terrà il seguente webinar:


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Tommaso RIGON (Duke University)


*A generalized Bayes framework for probabilistic clustering*


Abstract:

Clustering methods such as k-means and its variants are standard tools for
finding groups in the data. However, despite their huge popularity, the
underlying uncertainty can not be easily quantified. On the other hand,
mixture models represent a well-established inferential tool for
probabilistic clustering, but they are characterized by severe
computational bottlenecks and may have unreliable solutions in presence of
misspecifications. Instead, we rely on a generalized Bayes framework for
probabilistic clustering based on Gibbs posteriors. Broadly speaking, in
such a setting the log-likelihood is replaced by an arbitrary loss function
and this arguably leads to much richer families of clustering methods. Our
contribution is two-fold: first, we describe a clustering pipeline for
efficiently finding groups and then quantifying the associated uncertainty.
Second, we discuss two broad classes of loss functions which have
advantages in terms of analytic tractability and interpretability.
Specifically, we consider losses based on Bregman divergences and pairwise
dissimilarities and we show they can be interpreted as profile and
composite log-likelihoods, respectively. Full Bayesian inference is
conducted via Gibbs sampling but efficient deterministic algorithms are
available for point estimation.  As an important byproduct of our work, we
show that several existing clustering approaches can be interpreted as
generalized Bayesian estimators under specific loss functions. Hence, our
methodology can be also used to formally quantify the uncertainty in widely
used clustering approaches.

(joint work with Amy Herring and David Dunson, Duke University)

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Chiunque volesse collegarsi al webinar è pregato di inviare una email entro
mercoledi  27 Maggio a

pierpaolo.deblasi a unito.it


Il webinar è organizzato dalla "de Castro" Statistics Initiative

www.carloalberto.org/stats

in collaborazione con il Collegio Carlo Alberto.


Cordiali saluti,

Pierpaolo De Blasi

---
University of Torino & Collegio Carlo Alberto
carloalberto.org/pdeblasi
<https://sites.google.com/a/carloalberto.org/pdeblasi/>
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