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Graph Algorithms: Parallel computation

 
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Hi,
What are other  ways than the graph algorithms to implement in the area of AI or related?
 
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Hi Divya,

I'm not sure I totally understand your question, so let me know if I don't answer it.

Our focus is on graph algorithms that can be used for analysis or feature engineering.  We've seen graph features greatly improve the ROC curves for ML predictions and knowledge graphs help for adding more context to AI systems. In regards to features for training ML models, we see a lot of use of different community detection algorithms for fraud detection, centrality algos for finding influencer for recommendations, and a mix for disambiguations.  We also see quite a bit of use similarity and link prediction algorithms for feature engineering.

If you're interested in running ML/DL inside of a graph, this is a great paper on the concepts: https://blog.acolyer.org/2018/09/19/relational-inductive-biases-deep-learning-and-graph-networks/  (Note that I think we are several years from seeing this type of solution in the market.)
 
Divya Shiv
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Thank you for the explanation and  reference.
 
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