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Would You Have Clicked on What We Would Have Recommended?

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Summary

Peter B. Golbus describes recent work on the offline estimation of recommender system A/B tests using counterfactual reasoning techniques.

Bio

Peter B. Golbus is a Senior Data Scientist at Wayfair. Peter joined Wayfair directly from his Ph.D. program at Northeastern University where he studied the offline evaluation of search engines with Javed A. Aslam. Four years later, he is still at Wayfair, and is now studying the offline evaluation of recommender systems.

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PAPIs is the conference made by and for ML practitioners. Anyone can submit talk proposals (blind-reviewed by our committee) or ask questions to take discussions further. Breaks between sessions are perfect to get to know fellow attendees, speakers, and top ML companies.

Recorded at:

Mar 19, 2019

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