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What are a couple specific examples of how this has been useful at Yelp and Netflix?

What did you solve with MOE that would have been difficult to optimize by hand?



At Yelp we used MOE to tune the advertising system, optimizing thresholds for when to display certain types of ads, and how to rank the advertisements. More info can be found in this talk [1] and slides [2]. Tuning these thresholds across hundreds of categories, device types, and related dimensions would be impossible to do by hand, but is exactly what this system is built for.

Netflix has used MOE to optimize their deep learning systems (talk at MLconf [3], slides from NIPS [4]). Yelp was also able to leverage it to tune the hyperparameters of various machine learning systems in advertising and search.

SigOpt takes this work and related research and puts it behind an easy-to-use API and web interface. We want to bring these powerful tools to everyone and optimize everything.

[1]: https://www.youtube.com/watch?v=CC6qvzWp9_A

[2]: http://www.slideshare.net/YelpEngineering/optimal-learning-f...

[3]: https://www.youtube.com/watch?v=WdzWPuazLA8#t=24m55s

[4]: https://image.slidesharecdn.com/lessonslearnedpublic-1412132...




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