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Events for September 26, 2017

  • VIRTUAL Workshop: Get Connected for Maximum Job Search Success

    Tue, Sep 26, 2017 @ 02:00 PM - 03:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions

    Find out how to build relationships & connections to assist you in your academic career & in your job search. Develop the 30 Second Commercial you need to interact with employers.

    2 - 3 PM

    To join the webinar, go to https://bluejeans.com/8071179753 and log in using your NetID and password.

    Location: ONLINE

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

  • Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering

    Tue, Sep 26, 2017 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Evangelos Theodorou, Georgia Institute of Technology

    Talk Title: The Science of Autonomy: a \"Happy\" Symbiosis Among Learning, Control, and Physics

    Series: Fall 2017 Joint CSC@USC/CommNetS-MHI Seminar Series

    Abstract: In this talk, I will present an information theoretic approach to stochastic optimal control that has advantages over classical methodologies and theories for decision making under uncertainty. The main idea is that there are certain connections between optimality principles in control and information theoretic inequalities in statistical physics that allow us to solve hard decision making problems in robotics, autonomous systems and beyond. There are essentially two different points of view of the same \"thing\" and these two different points of view overlap for a fairly general class of dynamical systems that undergo stochastic effects. The information theoretic approach can also be used in a game theoretic setting for teams of robots performing cooperative or non-cooperative tasks. I will also present a holistic view to autonomy that collapses planning, perception and control into one computational engine, and ask questions related to how organization and structure relates to functionality and performance in \"engineered\" organisms. The last part of my talk includes computational frameworks for uncertainty representation and suggests ways to incorporate these representations within decision making and control.

    Biography: Evangelos A. Theodorou is an assistant professor with the Guggenheim School of aerospace engineering at Georgia Institute of Technology. He is also affiliated with the Institute of Robotics and Intelligent Machines. Evangelos Theodorou earned his Diploma in Electronic and Computer Engineering from the Technical University of Crete (TUC), Greece in 2001. He has also received a MSc in Production Engineering from TUC in 2003, a MSc in Computer Science and Engineering from University of Minnesota in spring of 2007 and a MSc in Electrical Engineering on dynamics and controls from the University of Southern California (USC) in Spring 2010. In May of 2011 he graduated with his PhD, in Computer Science at USC. After his PhD, he was a Postdoctoral Research Fellow with the department of computer science and engineering, University of Washington, Seattle. Evangelos Theodorou is the recipient of the King-Sun Fu best paper award of the IEEE Transactions on Robotics for the year 2012 and recipient of the best paper award in cognitive robotics in International Conference of Robotics and Automation 2011. He was also the finalist for the best paper award in International Conference of Humanoid Robotics in 2010 and International Conference of Robotics and Automation in 2017. His theoretical research spans the areas of stochastic optimal control theory, machine learning, information theory, and statistical physics. Applications involve learning, planning and control in autonomous, robotics and aerospace systems.

    Host: Mihailo Jovanovic, mihailo@usc.edu

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Contact: Gerrielyn Ramos

  • Epstein Institute Seminar, ISE 651

    Tue, Sep 26, 2017 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr. Nozer D. Singpurwalla, Emeritus Professor of Statistics and Distinguished Research Professor, George Washington University

    Talk Title: The Dinegentropy of Diagnostic and Detection Tests

    Host: Prof. Sheldon Ross

    More Information: September 26, 2017.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206

    Audiences: Everyone Is Invited

    Contact: Grace Owh

  • CS Colloquium: Kai-Wei Chang (UCLA) - Structured Predictions: Practical Advancements and Applications in Natural Language Processing

    Tue, Sep 26, 2017 @ 03:30 PM - 04:50 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Kai-Wei Chang, University of California, Los Angeles

    Talk Title: Structured Predictions: Practical Advancements and Applications in Natural Language Processing

    Abstract: This lecture satisfies requirements for CSCI 591: Research Colloquium.

    Many machine learning problems involve making joint predictions over a set of mutually dependent output variables. The
    dependencies between output variables can be represented by a structure, such as a sequence, a tree, a clustering of nodes, or a graph. Structured prediction models have been proposed for problems of this type, and they have been shown to be successful in many application areas, such as natural language processing, computer vision, and bioinformatics. In this talk, I will describe a collection of results that improve several aspects of these approaches. Our results lead to efficient learning algorithms for structured prediction models, which, in turn, support reduction in problem size, improvements in
    training and evaluation speed. I will also discuss potential risks and challenges when using structured prediction models.

    Related information is at https://urldefense.proofpoint.com/v2/url?u=http-3A__www.cs.virginia.edu_-7Ekc2wc_talk_sp.html&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=LW6zU4yKxktEWcUPnmtKow&m=gw-3C-3UJqv9mPCsdDWaZHFxfXoQ6oXlSMsVWGL1xE0&s=l7eOcCL3YxMMSSFD4dVdUUMKTrGVB5Z8Dm0VD1cHVDM&e=

    Biography: Kai-Wei Chang is an assistant professor in the Department of Computer Science at the University of California at Los Angeles. He has published broadly in machine learning and natural language processing. His research has mainly focused on designing machine learning methods for handling large and complex data. He has been involved in developing several machine learning libraries, including LIBLINEAR, Vowpal Wabbit, and Illinois-SL. He was an assistant professor at the University of Virginia in 2016-2017. He obtained his Ph.D. from the University of Illinois at Urbana-Champaign in 2015 and was a post-doctoral researcher at Microsoft Research in 2016. Kai-Wei was awarded the KDD Best Paper Award (2010), EMNLP Best Long Paper Award (2017), and the Yahoo! Key Scientific Challenges Award (2011).

    Additional information is available at https://urldefense.proofpoint.com/v2/url?u=http-3A__kwchang.net&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=LW6zU4yKxktEWcUPnmtKow&m=gw-3C-3UJqv9mPCsdDWaZHFxfXoQ6oXlSMsVWGL1xE0&s=wik3X8kutwqg-z2gIVP9M7W-uRkf04mPpX4HhWqxCDM&e=.

    Host: Fei Sha

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

  • Clark Construction Info Session

    Tue, Sep 26, 2017 @ 06:00 PM - 07:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions

    Clark Construction Information Session

    Location: Seeley G. Mudd Building (SGM) - 101

    Audiences: All Viterbi Students

    Contact: RTH 218 Viterbi Career Connections

  • Crowdstrike Cyber Security Tech Talk

    Tue, Sep 26, 2017 @ 06:30 PM - 08:00 PM

    Viterbi School of Engineering Student Organizations

    Workshops & Infosessions

    CrowdStrike was founded in 2011 to fix a fundamental problem: The sophisticated attacks that were forcing the world\'s leading businesses into the headlines could not be solved with existing malware-based defenses. Co-founders George Kurtz and Dmitri Alperovitch realized that a brand new approach was needed -- one that combines the most advanced endpoint protection with expert intelligence to pinpoint the adversaries perpetrating the attacks, not just the malware.

    CrowdStrike burst onto the national scene during the U.S. election season last year when it became the first to pin a data breach at the Democratic National Committee on Russia. They recently closed a $100 million funding round at a valuation exceeding $1 billion.


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    Location: James H. Zumberge Hall Of Science (ZHS) - 252

    Audiences: Everyone Is Invited

    Contact: USC CybOrg