Logo: University of Southern California

Events Calendar



Select a calendar:



Filter August Events by Event Type:



Events for August 27, 2018

  • Meet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Mon, Aug 27, 2018

    Viterbi School of Engineering Undergraduate Admission

    University Calendar


    This half day program is designed for prospective freshmen (HS juniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.

    Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.

    Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!

    RSVP

    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Everyone Is Invited

    Posted By: Viterbi Admission

    OutlookiCal
  • PhD Defense - Sara Marie McCarthy

    Mon, Aug 27, 2018 @ 10:00 AM - 12:00 PM

    Computer Science

    University Calendar



    Title: Hierarchical Planning in Security Games; A Game Theoretic Approach to Strategic, Tactical and Operational Decision Making

    Ph.D. Candidate: Sara Marie Mc Carthy

    Date and Time: Monday August 27th 2018, 10:00 AM EEB 132

    Committee: Milind Tambe, Phebe Vayanos, Eric Rice, Jonathan Gratch, Jelena Mirkovic

    Abstract:

    In the presence of an intelligent adversary, game theoretic models such as security games, have proven to be effective tools for mitigating risks from exploitable gaps in protection and security protocols, as they model the strategic interaction between an adversary and defender, and allow the defender to plan the use of scarce or limited resources in the face of such an adversary. However, standard security game models have limited expressivity in the types of planning they allow the defender to perform, as they look only at the deployment and allocation of a fixed set of security resources. This ignores two very important planning problems which concern the strategic design of the security system and resources to deploy as well as the usability and implementation of the security protocols. When these problems appear in real world systems, significant losses in utility and efficiency of security protocols can occur if they are not dealt with in a principled way.

    To address these limitations, in this thesis I introduce a new hierarchical structure of planning problems for security games, dividing the problem into three levels of planning (i) Strategic Planning, which considers long term planning horizons, and decisions related to game design which constrain the possible defender strategies, (ii) Tactical Planning, which considers shorter term horizons, dealing with the deployment of resources, and selection of defender strategies subject to strategic level constraints and (iii) Operational Planning, dealing with implementation of strategies in real world setting.

    First, focusing on Strategic Planning, I address the design problem of selecting a set of resource and schedule types. I introduce a new yet fundamental problem, the Simultaneous Optimization of Resource Teams and Tactics (SORT) which models the coupled problem of both strategic and tactical planning, optimizing over both game design with respect to selection of resource types, as well as their deployment actual in the field. I provide algorithms for efficiently solving the SORT problem, which use hierarchical relaxations of the optimization problem to compute these strategic level investment decisions. I show that this more expressive model allows the defender to perform more fine grained decision making that results in significant gains in utility. Second, motivated by the relevance and hardness of security games with resource heterogeneity, I also address challenges in tactical planning by providing a framework for computing adaptive strategies with heterogeneous resources. Lastly I look at the problem of operational planning, which has never been formally studied in the security game literature. I propose a new solution concept of operationalizable strategies, which randomize over an optimally chosen subset of pure strategies whose cardinality is selected by the defender. I show hardness of computing such operationalizable strategies and provide an algorithm for computing ε-optimal equilibria which are operationalizable.

    In all of these problems, I am motivated by real world challenges, and developing solution methods that are usable in the real world. As such much of this work has been in collaboration with organizations such as Panthera, WWF and other NGOs, to help protect the national parks and wildlife against deforestation and poaching, and the TSA, to protect critical infrastructure such as our airports from terrorist attacks. Because of this, in addressing these three levels of planning I develop solutions which are not only novel and academically interesting but also deployable with a real world impact.

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon

    OutlookiCal
  • Seminars in Biomedical Engineering

    Mon, Aug 27, 2018 @ 12:30 PM - 01:50 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Yang Yang, University of Southern California

    Talk Title: 3D Printing for Biomedical Applications

    Host: Qifa Zhou

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Posted By: Mischalgrace Diasanta

    OutlookiCal
  • Internship/Job Search Open Forum

    Mon, Aug 27, 2018 @ 01:00 PM - 02:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Increase your career and internship knowledge on the job/internship search by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners.

    For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: All Viterbi Students

    Posted By: RTH 218 Viterbi Career Connections

    OutlookiCal
  • CSC@USC/CommNetS-MHI Seminar Series

    Mon, Aug 27, 2018 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Jason Lee, University of Southern California

    Talk Title: Towards Theoretical Understanding of Over-Parametrization in Deep Learning

    Series: Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series

    Abstract: We provide new theoretical insights on why over-parametrization is effective in learning neural networks. For a k hidden node shallow network with quadratic activation and n training data points, we show that as long as k >= sqrt(2n) over-parametrization enables local search algorithms to find a globally optimal solution for general smooth and convex loss functions. Further, despite that the number of parameters may exceed the sample size, we show that with weight decay, the solution also generalizes well.

    Next, we analyze the implicit regularization effects of various optimization algorithms. In particular we prove that for least squares with mirror descent, the algorithm converges to the closest solution in terms of the Bregman divergence. For linearly separable classification problems, we prove that the steepest descent with respect to a norm solves SVM with respect to the same norm. For over-parametrized non-convex problems such as matrix sensing or neural net with quadratic activation, we prove that gradient descent converges to the minimum nuclear norm solution, which allows for both meaningful optimization and generalization guarantees.

    This is a joint work with Suriya Gunasekar, Mor Shpigel, Daniel Soudry, Nati Srebro, and Simon Du.

    Biography: Jason Lee is an assistant professor in Data Sciences and Operations at the University of Southern California. Prior to that, he was a postdoctoral researcher at UC Berkeley working with Michael Jordan. Jason received his PhD at Stanford University advised by Trevor Hastie and Jonathan Taylor. His research interests are in statistics, machine learning, and optimization. Lately, he has worked on high dimensional statistical inference, analysis of non-convex optimization algorithms, and theory for deep learning.



    Host: Mihailo Jovanovic, mihailo@usc.edu

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Gerrielyn Ramos

    OutlookiCal
  • CCI hosted event - ObEN will present "Personal AI on the Blockchain"

    Mon, Aug 27, 2018 @ 05:00 PM - 07:00 PM

    Ming Hsieh Department of Electrical Engineering

    Receptions & Special Events


    Please join CCI today, Monday, August 27th, 2018 from 5-7pm in the Michelson Building, MCB 101.

    ObEN will be presenting "Personal AI on the Blockchain."
    To RSVP and for more details, please register here: https://obenatusc.eventbrite.com

    Location: Michelson Center for Convergent Bioscience (MCB) - MCB 101

    Audiences: Everyone Is Invited

    Posted By: Brienne Moore

    OutlookiCal
  • Theta Tau Informational Session

    Mon, Aug 27, 2018 @ 07:00 PM - 09:00 PM

    Viterbi School of Engineering Student Organizations

    Workshops & Infosessions


    Learn what Theta Tau is all about in this informative presentation where you'll get the chance to ask any questions and talk to some of our actives. Food will be provided.

    Location: James H. Zumberge Hall Of Science (ZHS) - 352

    Audiences: Everyone Is Invited

    Posted By: Theta Tau

    OutlookiCal