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Events for April 09, 2013
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Viterbi-Gerontology Digital Aging Retreat
Tue, Apr 09, 2013 @ 09:00 AM - 12:30 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: ,
Talk Title:
Abstract: Interested faculty should contact Maja Mataric (mataric@usc.edu) as soon as possible.
Host: Maja Mataric
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: See details
Contact: Maja Mataric
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Nam Ma (USC), PhD Defense
Tue, Apr 09, 2013 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
Committee:
Aiichiro Nakano
Viktor K. Prasanna (Chairman)
Cauligi S. Raghavendra
Title: Scalable Exact Inference in Probabilistic Graphical Models on Multi-core Platforms
Abstract:
The recent switch to multi-core computing and the emergence of machine learning applications offer many opportunities for parallelization. A fundamental challenge is how to achieve scalability with the increasing number of cores. It is especially challenging for machine learning problems that have graph computational structure.
This thesis explores parallelism for exact inference in probabilistic graphical models to achieve scalable performance on multi-core platforms. Exact inference is widely used in probabilistic reasoning and machine learning. It also represents a large class of graph computations that have sophisticated computational patterns with large data sets. We propose parallel techniques to extract and exploit parallelism efficiently at multiple levels in the input graph.
• We first exploit parallelism available from the input graph using multithreading and task scheduling. At the node level, we explore data parallelism for the computational operations within a node. Data layout and data parallel algorithms are proposed for such node level computations. At the graph level, task parallelism is explored using directed acyclic graph (DAG) model. DAG scheduling is employed to efficiently map the tasks in the DAG to the hardware cores.
• In many cases, the input graph provides insufficient parallelism. To expose more parallelism, we study a relationship called 'weak dependency' between the tasks in a DAG. A novel DAG scheduling scheme is developed to exploit weak dependency for parallelism. In addition, pointer jumping technique is employed for exact inference when the input graph offers very limited parallelism due to its chain-like structure. With such explorations, a given fixed-size problem can still achieve high scalability with the increasing number of cores.
• In order to avoid the implementation complexity of many parallel techniques, we study the use of MapReduce as a high level programming model for exact inference. Our MapReduce-based algorithms for exact inference can also be applied for a class of graph computations with data dependency.
We implement and evaluate our techniques on state-of-the-art multi-core systems and demonstrate their scalability for a variety of input graphs.Location: Ronald Tutor Hall of Engineering (RTH) - 324
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Aditya Parameswaran (Stanford): Human-Powered Data Management
Tue, Apr 09, 2013 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Aditya Parameswaran, Stanford
Talk Title: Human-Powered Data Management
Series: CS Colloquium
Abstract: Fully automated algorithms are inadequate for a number of data analysis tasks, especially those involving images, video, or text. Thus, there is a need to combine "human computation" (or crowdsourcing), together with traditional computation, in order to improve the process of understanding and analyzing data. My thesis addresses several topics in the general area of human-powered data management. I design algorithms and systems for combining human and traditional computation for: (a) data processing, e.g., using humans to help sort, cluster, or clean data; (b) data extraction, e.g., having humans help create structured data from information in unstructured web pages; and (c) data gathering, i.e., asking humans to provide data that they know about or can locate, but that would be difficult to gather automatically. My focus in all of these areas is to find solutions that expend as few resources as possible (e.g., time waiting, human effort, or money spent), while still providing high quality results.
In this talk, I will first present a broad perspective of our research on human-powered data management, and I will describe some systems and applications that have motivated our research. I will then present details of one of the problems we have addressed: filtering large data sets with the aid of humans. Finally I will argue that human-powered data management is an area in its infancy, by describing a number of open problems I intend to address in my future research program.
Biography: Aditya Parameswaran is a Ph.D. student in the InfoLab at Stanford University, advised by Prof. Hector Garcia-Molina. He is broadly interested in data management, with research results in human computation, information extraction, and recommendation systems. Aditya is a recipient of the Key Scientific Challenges Award from Yahoo! Research (2010), two best-of-conference citations (VLDB 2010 and KDD 2012), and the Terry Groswith graduate fellowship at Stanford University.
Host: Cyrus Shahabi
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute / ISE 651 Seminar Series
Tue, Apr 09, 2013 @ 03:45 PM - 05:00 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: David Morton, Engineering Foundation Professor, Graduate Program in Operations Research & Industrial Engineering, Mechanical Engineering Department, The University of Texas at Austin
Talk Title: "Nested Solutions in Combinatorial Optimization"
Series: Epstein Institute Seminar Series
Abstract: We consider two classes of combinatorial optimization problems in which we maximize a gain function subject to a knapsack constraint. In the first class of models the gain function is supermodular and the knapsack constraint function is submodular and increasing. In the second class, the gain function is increasing and submodular and the knapsack constraint is simply a cardinality constraint. For both classes of models we focus on obtaining, in polynomial time, nested solutions to the parametric model under an increasing budget. We provide motivating examples involving border security, joint chance constraints, clustering, and rapidly detecting cell-phone viruses. This includes joint work with John Hasenbein, Jinho Lee, and Michael Nehme.
Biography: David Morton is Engineering Foundation Professor in the Graduate Program in Operations Research & Industrial Engineering in the Mechanical Engineering Department at The University of Texas at Austin. He has an MS and PhD in Operations Research from Stanford University and, prior to joining the faculty at UT-Austin, was a National Research Council Postdoctoral Fellow at the Naval Postgraduate School.
Host: Daniel J. Epstein Department of Industrial and Systems Engineering
More Information: Seminar-Morton.doc
Location: Von Kleinsmid Center For International & Public Affairs (VKC) - Room 100
Audiences: Everyone Is Invited
Contact: Georgia Lum
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Northrop Grumman Information Session
Tue, Apr 09, 2013 @ 06:00 PM - 08:00 PM
Viterbi School of Engineering Student Organizations
Student Activity
Northrop Grumman Information Session
Date: April 9th
Time: 6 PM
Place: THH 110
Please see the attached word document with more details on positions Northrop Grumman is actively recruiting.
Would you like to know how Northrop Grumman tackles challenging engineering problems to protect our nation's security? Northrop Grumman's Communication and Data Systems Center is coming for a Tech Talk to share how they work, in addition to meeting USC students with hopes of filling their open positions. In addition to other opportunities Northrop Grumman offers, their Comm. Center at NGAS is recruiting graduating BSEE and MSEE students for full time positions, so they would love to meet with you at the event!
Make sure to come out and network with Northrop Grumman representatives as they are looking for USC students to fill their ranks! Food will be provided, so come hungry and leave happy!
Location: Mark Taper Hall Of Humanities (THH) -
Audiences: Everyone Is Invited
Contact: Institute of Electrical and Electronics Engineers
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Study NightsTue, Apr 09, 2013 @ 07:00 PM - 10:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Come out to Study Nights and conquer your procrastination!
Group Study Rooms to work with your peers, quiet study spaces available, tutors, coffee, tea and snacks.
Sponsored by The Center for Engineering Diversity and The Viterbi Academic Resource Center.
Need more information? E-mail viterbi.ced@usc.edu.Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 111
Audiences: Everyone Is Invited
Contact: Center for Engineering Diversity
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USC Graduate Engineering Information Session in Germany(Hamburg)
Tue, Apr 09, 2013 @ 07:00 PM - 09:00 PM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Please join us for a Graduate Engineering Information Session hosted by Kelly Goulis, Senior Associate Dean of the USC Viterbi School of Engineering in Hamburg.
All students who have earned or are completing a Bachelor's degree in engineering, math or science are welcome to attend to learn more about graduate engineering programs at USC. Participants will also receive official brochures and handout information from USC.
Event will begin at 19:00 (CET-Hamburg time) and will take place at the
Fairmont Vier Jahreszeiten
Neuer Jungfernstieg 9-14
D-20354 Hamburg
Refreshments will be served. RSVP requestedAudiences: Everyone Is Invited
Contact: Viterbi Graduate & Professional Programs
