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Events for March 04, 2021

  • CS Colloquium: Abhinav Verma (University of Texas - Austin) - Neurosymbolic Reinforcement Learning

    Thu, Mar 04, 2021 @ 11:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Abhinav Verma, University of Texas - Austin

    Talk Title: Neurosymbolic Reinforcement Learning

    Series: CS Colloquium

    Abstract: Recent advances in Artificial Intelligence (AI) have been driven by deep neural networks. However, neural networks have certain well-known flaws: they are difficult to interpret and verify, have high variability, and lack domain awareness. These issues create a deficiency of trust and are hence a significant impediment to the deployment of AI in safety-critical applications. In this talk, I will present work that addresses these drawbacks via neurosymbolic learning in the reinforcement learning paradigm. Neurosymbolic agents combine experience based neural learning with partial symbolic knowledge expressed via programs in a Domain Specific Language (DSL). Using a DSL provides a principled mechanism to leverage high-level abstractionsfor machine learning models, and establishes a synergistic relationship between machine learning and program synthesis.

    To overcome the challenges of policy search in non-differentiable program space we introduce a meta-algorithm that is based on mirror descent, program synthesis, and imitation learning. This approach interleaves the use of synthesized symbolic programs to regularize neural learning with the imitation of gradient-based learning to improve the quality of synthesized programs. This perspective allows us to prove robust expected regret bounds and finite-sample guarantees for this algorithm. The theoretical results guaranteeing more reliable learning are accompanied by promising empirical results on complex tasks such as learning autonomous driving agents and generating interpretable programs for behavior annotation.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Abhinav Verma is a PhD Candidate at the University of Texas at Austin, where he is advised by Swarat Chaudhuri. His research lies at the intersection of machine learning and formal methods, with a focus on building intelligent systems that are reliable, transparent, and secure. His work builds connections between the symbolic reasoning and inductive learning paradigms of artificial intelligence. He is currently supported by a JP Morgan AI Research PhD Fellowship.

    Host: Mukund Raghothaman / Bistra Dilkina

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • Repeating EventUndergraduate Advisement Drop-in Hours

    Thu, Mar 04, 2021 @ 01:30 PM - 02:30 PM

    Thomas Lord Department of Computer Science

    Workshops & Infosessions


    Do you have a quick question? The CS advisement team will be available for drop-in live chat advisement for declared undergraduate students in our four majors during the spring semester on Tuesdays, Wednesdays, and Thursdays from 1:30pm to 2:30pm Pacific Time. Access the live chat on our website at: https://www.cs.usc.edu/chat/

    Location: Online

    Audiences: Undergrad

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    Contact: USC Computer Science

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  • ACM Facebook Engineers Panel

    Thu, Mar 04, 2021 @ 07:00 PM - 08:00 PM

    Thomas Lord Department of Computer Science

    Student Activity


    Facebook Engineers Panel:

    Want to learn about the opportunities Facebook has for you? Join ACM on Thursday, March 4, from 7-8 PM for a tech talk hosted by us and Facebook! Engineers and recruiters will be discussing their projects and experiences working at Facebook.

    Please fill out the RSVP form linked below. We will send the zoom link out to students who RSVP, so if you'd like to attend you must fill it out. Space is limited and will be filled on a first come first serve basis. This event is only open to undergraduate students. We hope to see you there!

    RSVP at https://forms.gle/q9qXY9UPVUv55MYa8

    Learn more at https://www.facebook.com/events/167553678371060/

    Location: Online - Zoom

    Audiences: Undergrad

    Contact: ACM

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