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Events for November 17, 2020

  • CS Colloquium: Mohammad Rostami (USC ISI) - Learning Efficiently in Data-Scarce Regimes

    Tue, Nov 17, 2020 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Mohammad Rostami, USC

    Talk Title: Learning Efficiently in Data-Scarce Regimes

    Abstract: The unprecedented processing demand, posed by the explosion of big data, challenges researchers to design efficient and adaptive machine learning algorithms that do not require persistent retraining and avoid learning redundant information. Inspired from learning techniques of intelligent biological agents, identifying transferable knowledge across learning problems has been a significant research focus to improve machine learning algorithms. In this talk, we explain how the challenges of knowledge transfer can be addressed through embedding spaces that capture and store hierarchical knowledge.

    We first focus on the problem of cross-domain knowledge transfer. We explore the problem of zero-shot image classification, where the goal is to identify images from unseen classes using semantic descriptions of these classes. We train two coupled dictionaries that align visual and semantic domains via an intermediate embedding space. We then extend this idea by training deep networks that match data distributions of two visual domains in a shared cross-domain embedding space.

    We then investigate the problem of cross-task knowledge transfer in sequential learning settings. Here, the goal is to identify relations and similarities of multiple machine learning tasks to improve performance across the tasks. We first address the problem of zero-shot learning in a lifelong machine learning setting, where the goal is to learn tasks with no data using high-level task descriptions. Our idea is to relate high-level task descriptors to the optimal task parameters through an embedding space. We then develop a method to overcome the problem of catastrophic forgetting within a continual learning setting of deep neural networks by enforcing the tasks to share the same distribution in the embedding space.

    Finally, we focus on current research directions to expand the past progress and plans for the future research directions. Through this talk, we demonstrate that despite major differences, problems within the above learning scenarios can be tackled using a unifying strategy that allows transferring knowledge effectively.

    This lecture satisfies requirements for CSCI 591: Research Colloquium


    Join Zoom Meeting
    https://usc.zoom.us/j/91954313931?pwd=U3JmUWR4WVZ6aDEyMUs0dEk0akZ5QT09

    Meeting ID: 919 5431 3931
    Passcode: 299776

    Biography: Mohammad Rostami is a computer scientist at USC Information Sciences Institute. He received Ph.D. degree in Electrical and Systems Engineering from the University of Pennsylvania in August 2019. He also received an M.S. degree in Robotics and M.A. degree in Philosophy at Penn. Before Penn, he obtained an M.Sc. degree in Electrical and Computer Engineering from University of Waterloo, and B.Sc. degree in Electrical Engineering and B.Sc. degree in Mathematics from the Sharif University of Technology. His current research area is learning in time-dependent and data-scarce regimes within machine learning.

    Host: CS Department

    Audiences: Everyone Is Invited

    Posted By: Cherie Carter

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  • ISE 651 - Epstein Seminar

    Tue, Nov 17, 2020 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Siqian Shen, Associate Professor, Industrial & Operations Engineering, University of Michigan

    Talk Title: Multistage Distributionally Robust Mixed-Integer Programming with Decision-Dependent Moment-Based Ambiguity Sets

    Host: Prof. Suvrajeet Sen

    More Information: November 17, 2020.pdf

    Location: Online/Zoom

    Audiences: Everyone Is Invited

    Posted By: Grace Owh

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  • CS Distinguished Lecture: Jennifer Rexford (Princeton University) - Securing Internet Applications From Routing Attacks

    Tue, Nov 17, 2020 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jennifer Rexford, Princeton University

    Talk Title: Securing Internet Applications From Routing Attacks

    Series: Computer Science Distinguished Lecture Series

    Abstract: The Internet is a "network of networks" that interconnects tens of thousands of separately administered networks. Yet, the Border Gateway Protocol (BGP), the glue that holds the disparate parts of the Internet together, is notoriously vulnerable to misconfiguration and attack. The consequences range from making destinations unreachable, to misdirecting traffic through unexpected intermediaries, to impersonating legitimate services. Attacks on Internet routing are typically viewed through the lens of availability and confidentiality, assuming an adversary that either discards traffic or performs eavesdropping. Yet, a strategic adversary can use routing attacks to compromise the security of critical Internet applications like Tor, certificate authorities, and the bitcoin network. In this talk, we survey such application-specific routing attacks and argue that both application-layer and network-layer defenses are essential and urgently needed. While application-layer defenses are easier to deploy in the short term, we hope that greater awareness of strategic attacks on important applications can provide much needed momentum for the deployment of network-layer defenses like secure routing protocols.

    Register in advance for this webinar at:

    https://usc.zoom.us/webinar/register/WN_uiLYEP8mRR2_UIQ4oJn5ug

    After registering, attendees will receive a confirmation email containing information about joining the webinar.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Jennifer Rexford is the Gordon Y.S. Wu Professor of Engineering and the Chair of Computer Science at Princeton University. Before joining Princeton in 2005, she worked for nine years at AT&T Labs--Research. Jennifer received her BSE degree in electrical engineering from Princeton University in 1991, and her PhD degree in electrical engineering and computer science from the University of Michigan in 1996. She is co-author of the book "Web Protocols and Practice" (Addison-Wesley, 2001). She served as the chair of ACM SIGCOMM from 2003 to 2007. Jennifer received ACM's Grace Murray Hopper Award for outstanding young computer professional, the ACM Athena Lecturer Award, the NCWIT Harrold and Notkin Research and Graduate Mentoring Award, the ACM SIGCOMM award for lifetime contributions, and the IEEE Internet Award. She is an ACM Fellow, an IEEE Fellow, and a member of the American Academy of Arts and Sciences, the National Academy of Engineering, and the National Academy of Sciences.


    Host: Heather Culbertson

    More Info: https://usc.zoom.us/webinar/register/WN_uiLYEP8mRR2_UIQ4oJn5ug

    Location: Online Zoom Webinar

    Audiences: Everyone Is Invited

    Posted By: Computer Science Department

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