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Events for April 01, 2016
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USC WiC: Visa Data Science Hackathon
Fri, Apr 01, 2016
Viterbi School of Engineering Student Organizations
Student Activity
***It is a 2 day Event - Apr 1 at 3 PM to Apr 2 at 3 PM***
USC Women in Computing is hosting a hackathon sponsored by Visa! Visa will be providing food, swag, prizes, and mentors during the hackathon. The event will last 24 hours starting Friday, April 1st at 3pm in VKC 100 and finishing Saturday, April 2nd at 3pm in VKC 261. Your hack can be anything data science related: data collection, processing, analysis, visualization, etc. Your teams can be 1-3 people. Winners will receive Beats headphones and an interview with Visa! We look forward to seeing you there :).
This event is open to all students.
More InfoLocation: Von Kleinsmid Center For International & Public Affairs (VKC) - 100 & 261
Audiences: Everyone Is Invited
Contact: Sanskriti
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AI SEMINAR
Fri, Apr 01, 2016 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Mahdi Soltanolkotabi, Assistant Professor at USC
Talk Title: Finding low-complexity models without the shackles of convexity
Series: AI Seminar
Abstract: In many applications, one wishes to estimate a large number of parameters from highly incomplete data samples. Low-dimensional models such as sparsity, low-rank, etc provide a principled approach for addressing the challenges posed by such high-dimensional data. The last decade has witnessed a flurry of activity in understanding when and how it is possible to find low complexity models via convex relaxations. However, the computational cost of such convex schemes can be prohibitive. In fact, in this talk I will argue that over insistence on convex methods has stymied progress in many application domains. I will discuss my ongoing research efforts to unshackle such problems from the confines of convexity opening the door for new applications.
I will discuss three concrete problems characterized by incomplete information about a low-complexity object of interest. The first is the century-old phase retrieval problem where one wishes to recover a signal from magnitude only measurements--phase information is completely missing. The second is a problem in data analysis, where we observe only a few incomplete linear measurements from a data matrix (e.g. a few entries) and wish to reliably infer all of the entries of the matrix. The third problem involves the recovery of a structured image from highly compressed information--most measurements are missing. To retrieve seemingly lost information I will present novel non-convex algorithms for these problems. Surprisingly, despite the lack of convexity these algorithms can provably converge to the global optimum and hence impute the missing information precisely.
Biography: Mahdi Soltanolkotabi completed his Ph.D. in electrical engineering at Stanford University in 2014. He was a postdoctoral researcher in the Algorithms, Machines, and People AMP lab and the EECS and Statistics departments at UC Berkeley during the 2014-2015 academic year. His research focuses on design and mathematical understanding of computationally efficient algorithms for optimization, high dimensional statistics, machine learning, signal processing and computational imaging. Recently, a main focus of his research has been on developing and analyzing algorithms for non-convex optimization with provable guarantees of convergence to the global optimum.
WILL NOT BE WEBCASTED
Host: Emilio Ferrara
Location: Information Science Institute (ISI) - 1135 - 11th fl Large CR
Audiences: Everyone Is Invited
Contact: Alma Nava / Information Sciences Institute
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Apr 01, 2016 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Helen Park, from WET Design, titled "When Engineering Meets Design."
Location: Seeley G. Mudd Building (SGM) - 123
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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NL Seminar-Harnessing reviews to build richer models of opinions
Fri, Apr 01, 2016 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Julian McAuley , UCSD
Talk Title: Harnessing reviews to build richer models of opinions
Series: Natural Language Seminar
Abstract: Online reviews are often our first port of call when considering products and purchases online. Yet navigating huge volumes of reviews (many of which we might disagree with) is laborious, especially when we are interested in some niche aspect of a product. This suggests a need to build models that are capable of capturing the complex and idiosyncratic semantics of reviews, in order to build richer and more personalized recommender systems. In this talk I'll discuss three such directions: First, how can reviews be harnessed to better understand the dimensions (or facets) of people's opinions? Second, how can reviews be used to answer targeted questions, that may be subjective or require personalized responses? And third, how can reviews themselves be synthesized, so as to predict what a reviewer would say, even for products they haven't seen yet?
Biography: Dr. McAuley has been an Assistant Professer in the Computer Science Department at the University of California, San Diego since 2014. Previously he was a postdoctoral scholar at Stanford University after receiving his PhD from the Australian National University in 2011. His research is concerned with developing predictive models of human behavior using large volumes of online activity data.
Host: Xing Shi and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
