Connectionists: Graph Machine Learning in Industry Webinar

[david rohde]

Criteo AI Lab is excited to be presenting Graph Machine Learning in
Industry. Please join us on *Thursday, September 23rd, at 17:00 Paris time*.

Registration is now open:
https://sites.google.com/view/graph-ml-in-industry/home



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.



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.



In this spirit, the goal of *Graph Machine Learning in Industry* 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.

Speakers:

   - James Zhang (AWS)
   - Charles Tapley Hoyt (Harvard Medical School)
   - Anton Tsitsulin (Google)
   - Cheng Ye (AstraZeneca)
   - Rocío Mercado (MIT)
   - Lingfei Wu (JD.com)
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