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[34] Sasha Rush - Lagrangian Relaxation for Natural Language Decoding

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Manage episode 305017413 series 2982803
Content provided by The Thesis Review and Sean Welleck. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Thesis Review and Sean Welleck or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Sasha Rush is an Associate Professor at Cornell Tech and researcher at Hugging Face. His research focuses on building NLP systems that are safe, fast, and controllable. Sasha's PhD thesis is titled, "Lagrangian Relaxation for Natural Language Decoding", which he completed in 2014 at MIT. We talk about his work in the thesis on decoding in NLP, how it connects with today, and many interesting topics along the way such as the role of engineering in machine learning, breadth vs. depth, and more. - Episode notes: https://cs.nyu.edu/~welleck/episode34.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
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47 episodes

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Manage episode 305017413 series 2982803
Content provided by The Thesis Review and Sean Welleck. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Thesis Review and Sean Welleck or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Sasha Rush is an Associate Professor at Cornell Tech and researcher at Hugging Face. His research focuses on building NLP systems that are safe, fast, and controllable. Sasha's PhD thesis is titled, "Lagrangian Relaxation for Natural Language Decoding", which he completed in 2014 at MIT. We talk about his work in the thesis on decoding in NLP, how it connects with today, and many interesting topics along the way such as the role of engineering in machine learning, breadth vs. depth, and more. - Episode notes: https://cs.nyu.edu/~welleck/episode34.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
  continue reading

47 episodes

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