<div dir="ltr"><div class="gmail_quote gmail_quote_container"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><br>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;line-height:115%">Dear colleagues, </span></p>

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<p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt">Our next seminar will be
held on Monday, <b>June 23</b>,<b> </b>from <b>3:30
p.m. to 4:30 p.m</b>. (Rio de Janeiro local time).  The meeting will take place at room </span><b><span lang="EN-US" style="font-size:12pt">C116-
Bloco C - CT</span></b><b><span lang="DE" style="font-size:12pt"> – Instituto de Matemática – UFRJ. </span></b><span lang="DE" style="font-size:12pt">There will be no transmission
online. </span><b><span lang="EN-US" style="font-size:12pt"></span></b></p>

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<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;line-height:115%;color:black">Speaker: <b>  Marina Silva Paez (IM-UFRJ)</b></span></p>

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<p class="MsoNormal" style="line-height:normal;margin:0in 0in 10pt;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Title: <b>Hierarchical
stochastic block model for community detection in multiplex networks</b></span></p>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Abstract: Multiplex networks have
become increasingly more prevalent in many fields, and have emerged as a
powerful tool for modeling the complexity of real networks. There is a critical
need for developing inference models for multiplex networks that can take into
account potential dependencies across different layers, particularly when the
aim is community detection.  We add to a limited literature by proposing a
novel and efficient Bayesian model for community detection in multiplex
networks. A key feature of our approach is the ability to model varying
communities at different network layers. In contrast, many existing models
assume the same communities for all layers. Moreover, our model
automatically picks up the necessary number of communities at each layer (as
validated by real data examples). This is appealing, since deciding the number
of communities is a challenging aspect of community detection, and especially
so in the multiplex setting, if one allows the communities to change across
layers.  Borrowing ideas from hierarchical Bayesian modeling, we use a
hierarchical Dirichlet prior to model community labels across layers, allowing
dependency in their structure.  Given the community labels, a stochastic
block model (SBM) is assumed for each layer. We develop an efficient slice
sampler for sampling the posterior distribution of the community labels as well
as the link probabilities between communities. In doing so, we address some
unique challenges posed by coupling the complex likelihood of SBM with the
hierarchical nature of the prior on the labels.  An extensive empirical validation
is performed on simulated and real data, demonstrating the superior performance
of the model over single-layer alternatives, as well as the ability to uncover
interesting structures in real networks. </span></p>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Joint work with Arash Amini 
(UCLA), Marina Paez (UFRJ) e Lizhen Lin (University of Maryland)</span></p>

<p class="MsoNormal" style="line-height:normal;margin:0in 0in 10pt;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt">More complete information
about the seminars can be found at</span></p>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US"><a href="https://ppge.im.ufrj.br/seminarios-de-probabilidade/" target="_blank">https://ppge.im.ufrj.br/seminarios-de-probabilidade/</a></span></p>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;line-height:115%">Sincerely, </span><span lang="EN-US" style="font-size:12pt;line-height:115%"></span></p>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;line-height:115%">Organizers: Giulio Iacobelli and Maria Eulalia
Vares</span></p>

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<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;line-height:115%"> </span></p>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12pt;line-height:115%"> </span></p>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US"> </span></p>

<p class="MsoNormal" style="margin:0in 0in 10pt;line-height:115%;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-US"> </span></p></div></div></div>
</div><div><br></div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><br></div></div></div></div>
</div><div><br clear="all"></div><div><br></div><span class="gmail_signature_prefix">-- </span><br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr">Maria Eulalia Vares<div>Professora Titular - Instituto de Matemática - UFRJ</div><div>Coordenadora do Programa de Pós-Graduação em Estatística</div><div><a href="https://ppge.im.ufrj.br/" target="_blank">https://ppge.im.ufrj.br/</a></div><div><br></div></div></div></div>
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