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  • NL Seminar-INTERACTIVELY TEACHING MACHINES WITH NATURAL LANGUAGES

    Thu, May 06, 2021 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Zhou Yu , Columbia University

    Talk Title: INTERACTIVELY TEACHING MACHINES WITH NATURAL LANGUAGES

    Abstract: Reminder Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you're highly encouraged to use your USC account to sign into Zoom. If you're an outside visitor, please inform nlg-seminar-admin2@isi.edu beforehand so we'll be aware of your attendance and let you in.

    Abstract:
    Humans routinely learn new concepts using natural language communications, even in scenarios with limited or no labeled examples. Interactions are another key aspect of human learning as well. Learning to ask good questions is a key step towards effective learning. Can machines do the same? In this talk, we will talk about how can a machine learn to ask good natural language questions and plan dynamically what questions to ask next to learn tasks effectively in low-resource settings.


    Biography: Zhou Yu joined the CS department at Columbia University in Jan 2021 as an Assistant Professor. Before that, she was an Assistant Professor at UC Davis. She obtained her Ph.D. from Carnegie Mellon University in 2017. Zhou has built various dialog systems that have a real impact, such as a job interview training system, a depression screening system, and a second language learning system. Her research interest includes dialog systems, language understanding and generation, vision and language, human computer interaction, and social robots. Zhou received an ACL 2019 best paper nomination, featured in Forbes 2018 30 under 30 in Science, and won the 2018 Amazon Alexa Prize.

    Host: Jon May and Mozhdeh Gheini

    More Info: https://nlg.isi.edu/nl-seminar/

    Webcast: https://youtu.be/rNyOspG27Xs

    Location: Information Science Institute (ISI) - Virtual Only

    WebCast Link: https://youtu.be/rNyOspG27Xs

    Audiences: Everyone Is Invited

    Contact: Petet Zamar

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