[07] John Schulman - Optimizing Expectations: From Deep RL To Stochastic Computation Graphs The Thesis Review podcast

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Science Thesis Review Sean Welleck

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[07] John Schulman - Optimizing Expectations: From Deep RL to Stochastic Computation Graphs

for 5 år siden 1:04:28

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Indhold leveret af The Thesis Review and Sean Welleck. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Thesis Review and Sean Welleck eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

John Schulman is a Research Scientist and co-founder of Open AI. John co-leads the reinforcement learning team, researching algorithms that safely and efficiently learn by trial and error and by imitating humans. His PhD thesis is titled "Optimizing Expectations: From Deep Reinforcement Learning to Stochastic Computation Graphs", which he completed in 2016 at Berkeley. We talk about his work on stochastic computation graphs and TRPO, how it evolved to PPO and how it's used in large-scale applications like Open AI Five, as well as his recent work on generalization in RL. Episode notes: https://cs.nyu.edu/~welleck/episode7.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview

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49 episoder

#Science #Thesis Review #Sean Welleck

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[07] John Schulman - Optimizing Expectations: From Deep RL to Stochastic Computation Graphs

The Thesis Review

published for 5 år siden

Del

MP3•Episode hjem

Indhold leveret af The Thesis Review and Sean Welleck. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Thesis Review and Sean Welleck eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

John Schulman is a Research Scientist and co-founder of Open AI. John co-leads the reinforcement learning team, researching algorithms that safely and efficiently learn by trial and error and by imitating humans. His PhD thesis is titled "Optimizing Expectations: From Deep Reinforcement Learning to Stochastic Computation Graphs", which he completed in 2016 at Berkeley. We talk about his work on stochastic computation graphs and TRPO, how it evolved to PPO and how it's used in large-scale applications like Open AI Five, as well as his recent work on generalization in RL. Episode notes: https://cs.nyu.edu/~welleck/episode7.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview

… continue reading

49 episoder

#Science #Thesis Review #Sean Welleck

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