<div dir="ltr"><p class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">Criteo AI
Lab is excited to be presenting Graph Machine Learning in Industry. Please join
us on <b>Thursday, September 23rd, at 17:00 Paris time</b>.<br>
<br>
Registration is now open: <a href="https://sites.google.com/view/graph-ml-in-industry/home" target="_blank" style="color:rgb(5,99,193)"><span style="color:rgb(26,115,232);text-decoration-line:none">https://sites.google.com/view/graph-ml-in-industry/home</span></a></span></p>

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<p class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">Many
problems in data mining, machine learning, and computer science can be
formulated as graph problems. From modelling relationships in social networks
and recommender systems to identifying the strengths of molecule reactions,
graphs are a natural way to represent certain systems. Research into this area
has recently demonstrated the viability of this approach with many recent
success stories.  </span></p>

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<p class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">At the
same time, research and deployment of graph machine learning solutions in an
industrial setting present new and unique challenges. These include training
the models at scale, dealing with heterogeneous data format, storing and
updating large graphs, identifying new applications, among many others.</span></p>

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<p class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">In this
spirit, the goal of <b>Graph Machine Learning in Industry</b> workshop
is to gather the community of graph practitioners in the industry and to
present recent ML solutions that are successful in solving real-world problems.<br>
<br>
Speakers:</span></p>

<ul type="disc" style="margin-bottom:0cm">
 <li class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">James
     Zhang (AWS)</span></li>
 <li class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">Charles
     Tapley Hoyt (Harvard Medical School)</span></li>
 <li class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">Anton
     Tsitsulin (Google)</span></li>
 <li class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">Cheng
     Ye (AstraZeneca)</span></li>
 <li class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">Rocío
     Mercado (MIT)</span></li>
 <li class="MsoNormal" style="margin:0cm;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:10.5pt;font-family:Roboto">Lingfei
     Wu (JD.com)</span></li>
</ul></div>