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Events for October 11, 2012
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Mock Interviews offered by Target
Thu, Oct 11, 2012 @ 11:00 AM - 01:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Sign Up In RTH 218 today to participate! Join Target representatives to take advantage of this opportunity to practice your interview skills.
Mock interviews by appointment only Thu, Oct 11, 2012 @ 11:00 AM - 01:00 PM
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi BS, MS Students
Contact: RTH 218 Viterbi Career Services
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Nanoscale Surface Engineering by Atomic and Molecular Layer Deposition
Thu, Oct 11, 2012 @ 12:45 PM - 02:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Gregory Parsons, Chemical and Biomolecular Engineering Department, North Carolina State University
Series: Distinguished Lectures Series
Location: James H. Zumberge Hall Of Science (ZHS) - 159
Audiences: Everyone Is Invited
Contact: Ryan Choi
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PhD Application Process: Writing a Personal Statement
Thu, Oct 11, 2012 @ 03:30 PM - 05:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Workshops & Infosessions
This 5-part workshop is designed to introduce Viterbi undergraduates to the purpose of a pursuing a PhD, and aid in their PhD application process. All Viterbi majors are invited to attend one or more workshops.
One of the key parts of your graduate school application is your personal statement. We will review the doâs and donâts of writing a personal statement, and review the critical points which you need to make sure to address in your statement.
Previous Workshops:
PhD Programs: 9/20
GRE Preparation: 9/27
Choosing a School/Advisor: 10/4
Upcoming Workshops
Preparing a CV: 10/18
Material from previous workshops is available at: http://armani.usc.eduMore Information: Fall seminar series.pdf
Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116
Audiences: Undergrad
Contact: Andrea Armani
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CS Colloquium: Jun Zhu: Bayesian Inference with Max-margin Posterior Regularization
Thu, Oct 11, 2012 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Jun Zhu, Tsinghua University
Talk Title: Bayesian Inference with Max-margin Posterior Regularization
Series: CS Colloquium
Abstract: Existing Bayesian models, especially nonparametric Bayesian methods, rely heavily on specially conceived priors to incorporate domain knowledge for discovering improved latent representations. While priors can affect posterior distributions through Bayes' theorem, imposing posterior regularization is arguably more direct and in some cases can be more natural and easier. In this talk, I will present regularized Bayesian inference (RegBayes), a computational framework to perform posterior inference with a convex regularization on the desired post-data posterior distributions. When the convex regularization is induced from a linear operator on the posterior distributions, RegBayes can be solved with convex analysis theory. Furthermore, I will present some concrete examples, including MedLDA for learning discriminative topic representations and infinite latent support vector machines for learning discriminative latent features for classification. All these models explore the large-margin idea in combination with a (nonparametric) Bayesian model for discovering predictive latent representations. I will discuss both variational and Monte Carlo methods for approximate inference.
Biography: Dr. Jun Zhu is an associate professor in the Department of Computer Science and Technology at Tsinghua University. His principal research interests lie in the development of statistical machine learning methods for solving scientific and engineering problems arising from artificial and biological learning, reasoning, and decision-making in the high-dimensional and dynamic worlds. Prof. Zhu received his Ph.D. in Computer Science from Tsinghua University, and his advisor was Prof. Bo Zhang. He did post-doctoral research with Prof. Eric P. Xing in the Machine Learning Department at Carnegie Mellon University. His current work involves both the foundations of statistical learning, including theory and algorithms for probabilistic latent variable models, sparse learning in high dimensions, Bayesian nonparametrics, and large-margin learning; and the application of statistical learning in social network analysis, data mining, and multi-media data analysis.
http://www.ml-thu.net/~jun/
Host: Fei Sha
More Info: http://www.cs.usc.edu/calendar/csevents.asp?date=10%2F11%2F2012
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: http://www.cs.usc.edu/calendar/csevents.asp?date=10%2F11%2F2012
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Raytheon Information Session
Thu, Oct 11, 2012 @ 05:30 PM - 07:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Join representatives of this company as they share general company information and available opportunities.
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 106
Audiences: All Viterbi BS, MS Students
Contact: RTH 218 Viterbi Career Services
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EE 101 Supplemental Instruction SessionThu, Oct 11, 2012 @ 07:00 PM - 09:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Supplemental Instruction session for students enrolled in EE 101.
SI offers an informal atmosphere where you and your classmates can explore important concepts, review class notes, discuss assignments, work on practice problems, and go over relevant study skills.
SI is a great study option and we encourage all students to make SI part of their study habits! Come for 30 minutes or the whole 2 hours.Location: Kaprielian Hall (KAP) - 144
Audiences: Undergrad
Contact: Viterbi Academic Resource Center
