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[14] Been Kim - Interactive and Interpretable Machine Learning Models
MP3•Thuis aflevering
Manage episode 302418431 series 2982803
Inhoud geleverd door The Thesis Review and Sean Welleck. Alle podcastinhoud, inclusief afleveringen, afbeeldingen en podcastbeschrijvingen, wordt rechtstreeks geüpload en geleverd door The Thesis Review and Sean Welleck of hun podcastplatformpartner. Als u denkt dat iemand uw auteursrechtelijk beschermde werk zonder uw toestemming gebruikt, kunt u het hier beschreven proces https://nl.player.fm/legal volgen.
Been Kim is a Research Scientist at Google Brain. Her research focuses on designing high-performance machine learning methods that make sense to humans. Been's PhD thesis is titled "Interactive and Interpretable Machine Learning Models for Human Machine Collaboration", which she completed in 2015 at MIT. We discuss her work on interpretability, including her work in the thesis on the Bayesian Case Model and its interactive version, as well as connections with her subsequent work on black-box interpretability methods that are used in many real-world applications. Episode notes: https://cs.nyu.edu/~welleck/episode14.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
47 afleveringen
MP3•Thuis aflevering
Manage episode 302418431 series 2982803
Inhoud geleverd door The Thesis Review and Sean Welleck. Alle podcastinhoud, inclusief afleveringen, afbeeldingen en podcastbeschrijvingen, wordt rechtstreeks geüpload en geleverd door The Thesis Review and Sean Welleck of hun podcastplatformpartner. Als u denkt dat iemand uw auteursrechtelijk beschermde werk zonder uw toestemming gebruikt, kunt u het hier beschreven proces https://nl.player.fm/legal volgen.
Been Kim is a Research Scientist at Google Brain. Her research focuses on designing high-performance machine learning methods that make sense to humans. Been's PhD thesis is titled "Interactive and Interpretable Machine Learning Models for Human Machine Collaboration", which she completed in 2015 at MIT. We discuss her work on interpretability, including her work in the thesis on the Bayesian Case Model and its interactive version, as well as connections with her subsequent work on black-box interpretability methods that are used in many real-world applications. Episode notes: https://cs.nyu.edu/~welleck/episode14.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
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