Colloquia

2021 Apr 19

Statistics Colloquium: Alexandre Belloni (Duke University)

10:30am to 11:30am

Location: 

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

Title:

Subvector Inference in Partially Identified Models with Many Moment Inequalities

Abstract:

In this work we consider bootstrap-based inference methods for functions of the parameter vector in the presence of many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. In particular this covers the case of subvector inference, such as the inference on a single component associated with a...

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2021 Apr 05

Statistics Colloquium: Xiaotong Shen (University of Minnesota)

10:30am to 11:30am

Location: 

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

Title:

Inference for a directed acyclic graphical model with interventions

Abstract:

Consider an inference problem in a directed acyclic graphical model subject to unknown interventions. In this presentation, we will give conditions for multiple unknown interventions to yield an identifiable model. For inference, we identify...

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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...

Read more about Statistics Colloquium: Julia Palacios (Stanford University)
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...

Read more about Statistics Colloquium: Francois Caron (University of Oxford)

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