Off-Line, Off-Policy RL for Real-World Decision Making at Facebook - #448

Off-Line, Off-Policy RL for Real-World Decision Making at Facebook - #448

Today we’re joined by Jason Gauci, a Software Engineering Manager at Facebook AI. In our conversation with Jason, we explore their Reinforcement Learning platform, Re-Agent (Horizon). We discuss the role of decision making and game theory in the platform and the types of decisions they’re using Re-Agent to make, from ranking and recommendations to their eCommerce marketplace. Jason also walks us through the differences between online/offline and on/off policy model training, and where Re-Agent sits in this spectrum. Finally, we discuss the concept of counterfactual causality, and how they ensure safety in the results of their models. The complete show notes for this episode can be found at twimlai.com/go/448.

Episoder(779)

Learning Active Learning with Ksenia Konyushkova - TWiML Talk #116

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Inverse Programming for Deeper AI with Zenna Tavares - TWiML Talk #114

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26 Feb 201828min

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In this episode, I speak with Sriraam Natarajan, Associate Professor in the Department of Computer Science at UT Dallas. While at NIPS a few months back, Sriraam and I sat down to discuss his work on ...

23 Feb 201847min

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20 Feb 201848min

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Learning "Common Sense" and Physical Concepts with Roland Memisevic - TWiML Talk #111

In today’s episode, I’m joined by Roland Memisevic, co-founder, CEO, and chief scientist at Twenty Billion Neurons. Roland joined me at the RE•WORK Deep Learning Summit in Montreal to discuss the work...

15 Feb 201832min

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In this episode, the third in our Black in AI series, I speak with Ayanna Howard, Chair of the Interactive School of Computing at Georgia Tech. Ayanna joined me for a lively discussion about her work ...

13 Feb 201846min

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For today’s show, I'm joined by Nyalleng Moorosi, Senior Data Science Researcher at The Council for Scientific & Industrial Research or CSIR, in Pretoria, South Africa. In our discussion, we discuss t...

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