Colloquia

2021 Feb 22

Statistics Colloquium: Julia Palacios (Stanford University)

10:30am to 11:30am

Location: 

Zoom - please contact emilie_campanelli@fas.harvard.edu for more information

Title:

Distance-based summaries and modeling of evolutionary trees

Abstract:

Ranked tree shapes are mathematical objects of great importance used to model hierarchical data and evolutionary processes with applications ranging across many fields including evolutionary biology and infectious disease transmission.  While...

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2020 Nov 09

Statistics Colloquium: Alexandra Carpentier (Otto-von-Guericke-Universität Magdeburg)

10:30am to 11:30am

Location: 

Zoom - please contact emilie_campanelli@fas.harvard.edu for more information

Title:

Several structured thresholding bandit problem

Abstract:

In this talk we will discuss the thresholding bandit problem, i.e. a sequential learning setting where the learner samples sequentially K unknown distributions for T times, and aims at outputting at the end the set of distributions whose means\(\mu_k\) are above a threshold \(\tau\). We will study this problem under four structural assumptions, i.e. shape constraints: that the sequence of means is monotone, unimodal...

Read more about Statistics Colloquium: Alexandra Carpentier (Otto-von-Guericke-Universität Magdeburg)
2020 Oct 26

Statistics Colloquium: Francois Caron (University of Oxford)

10:30am to 11:30am

Location: 

Zoom - please contact emilie_campanelli@fas.harvard.edu for more information

Title:

Non-exchangeable random partition models for microclustering

Abstract:

Many popular random partition models, such as the Chinese restaurant process and its two-parameter extension, fall in the class of exchangeable random partitions, and have found wide applicability in model-based clustering, population genetics, ecology or network analysis. While the exchangeability assumption is sensible in many cases, it has some strong implications. In particular, Kingman’s representation theorem implies that the size of the clusters...

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