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[32] Andre Martins - The Geometry of Constrained Structured Prediction
Manage episode 302418413 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.
Andre Martins is an Associate Professor at IST and VP of AI Research at Unbabel in Lisbon, Portugal. His research focuses on natural language processing and machine learning. Andre’s PhD thesis is titled, "The Geometry of Constrained Structured Prediction: Applications to Inference and Learning of Natural Language Syntax", which he completed in 2012 at Carnegie Mellon University and IST. We talk about his work in the thesis on structured prediction in NLP, and discuss connections between his thesis work on later work on sparsity, sparse communication, and more. - Episode notes: https://cs.nyu.edu/~welleck/episode32.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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Manage episode 302418413 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.
Andre Martins is an Associate Professor at IST and VP of AI Research at Unbabel in Lisbon, Portugal. His research focuses on natural language processing and machine learning. Andre’s PhD thesis is titled, "The Geometry of Constrained Structured Prediction: Applications to Inference and Learning of Natural Language Syntax", which he completed in 2012 at Carnegie Mellon University and IST. We talk about his work in the thesis on structured prediction in NLP, and discuss connections between his thesis work on later work on sparsity, sparse communication, and more. - Episode notes: https://cs.nyu.edu/~welleck/episode32.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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Get in-depth coverage of current and future trends in technology, and how they are shaping business, entertainment, communications, science, politics, and society.
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