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Conferences, Lectures, & Seminars
Events for April
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AI SEMINAR
Fri, Apr 04, 2014 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Laila Sakr , University of Southern Californiaââ¬â¢s School of Cinematic Arts
Talk Title: /sentiment analysis_fail
Series: AISeminar
Abstract: Abstract:This presentation traces the evolution of a digital archive to a machine learning, knowledge management system. R-Shief.org houses four data collections, current search engine (Kal3a), Arab Smart Engine, interactive visualizers, and index. In this talk, I will discuss the challenges to normalize uneven data inputs into one system or database. This requires building a network where each data point has its position and function in relation to all the other data points. When the size, speed, and variety of the data reaches a threshold, new, creative methods are developed to keep all the pieces working together. It is in the relationality of the data to each other where machine learning can take place and programs can be built to be ââ¬Åsmart.ââ¬Â By 2014, I would say that the methodological shift to using big data in textual analysis in the humanities has meant a shift from big data to smart data--or big, smart data. will provide a vision of a body of work at the intersection of technology, media arts, and politics. The data visualizations, social media analytics, interactive media, VJ performances, and computational art showcased are poised between multiple worlds (art/science, culture/technology, east/west, macro/micro, history/real-time, theory/practice, scholarship/activism).
Biography: Bio: Laila Shereen Sakr is VJ Um Amel online. She is a PhD candidate in Media Arts + Practice at the University of Southern Californiaââ¬â¢s School of Cinematic Arts and founder of the digital lab, R-Shief, Inc. With a background in poetry and graphic design, her current practices include digital media arts, visualization, and performance. Her work archives and maps the recent Arab uprisings and Occupy movements through semantic analysis of social media feeds in Arabic, Persian, French, English, Spanish, German. As a VJ, she uses data visualization and live cinema performance to demonstrate how embodied habits of communication are expressed virtually, and to understand how communities use technology to design their own narratives and worlds. She has exhibited at the San Francisco MoMA, National Gallery of Art in Jordan, Camera Austria, Cultura Digital in Brazil, DC Fridge Art Gallery, among other venues. Her work has also been published in Middle East Critique, Parsonââ¬â¢s Journal for Information Mapping, ThoughtMesh, Jadaliyya, and in an edited volume on Mediating the Arab Uprisings. She holds an M.F.A. in Digital Arts and New Media from University of California, Santa Cruz and an M.A. in Arab Studies from Georgetown University. Recent reviews appear in The Wall Street Journal, Science, Art Territories, Fast Company, Digital Media and Learning, Egypt Independent, and The Creators Project. http://vjumamel.com
Caption for image: Tweet World: A 3D Game in Unity transforms a 2D data visualization of 500,000 tweets on #Syria into a 3D immersive environment
Host: Greg Ver Steeg
Webcast: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=be33305d8976432d85f08102899de2ca1dLocation: Information Science Institute (ISI) - 1135
WebCast Link: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=be33305d8976432d85f08102899de2ca1d
Audiences: Everyone Is Invited
Contact: Alma Nava / Information Sciences Institute
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
AI SEMINAR
Fri, Apr 11, 2014 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Shaddin Dughmi, USC Computer Science
Talk Title: On the hardness of signaling
Series: AISeminar
Abstract: There has been a recent surge of interest in algorithmic questions relating to information revelation in games and auctions. Given that equilibrium outcomes of a game are intimately related to the beliefs of its participants, how should a "market maker" with access to additional information, and equipped with a specified objective, inform players in the game? We consider the computational complexity of two of the simplest instantiations of this question: (1) A Bayesian zero-sum game in which the principal must choose an information structure maximizing the equilibrium payoff of one ofthe players; (2) A single-item auction in which the seller possesses additional information regarding the item for sale, and must release, subject to a communication constraint, information regarding the item so as to maximize the resulting welfare at equilibrium. In both cases, we show that optimal signaling is computationally intractable, and in fact hard to approximate, assuming that it is hard to recover a planted dense subgraph in a random undirected graph.
Biography: Shaddin Dughmi is an Assistant Professor in the Department of Computer Science at USC, where he is a member of the Theory Group. He received a B.S. in computer science, summa cum laude, from Cornell University in 2004, and a PhD in computer science from Stanford University in 2011. He is a recipient of the NSF CAREER award, the Arthur L. Samuel best doctoral thesis award, and the ACM EC best student paper award.
Host: Greg Ver Steeg
More Info: PER SPEAKER'S REQUEST, THIS WILL NOT BE WEBCASTED
Webcast: PER SPEAKER'S REQUEST, THIS WILL NOT BE WEBCASTEDLocation: Information Science Institute (ISI) - 1135
WebCast Link: PER SPEAKER'S REQUEST, THIS WILL NOT BE WEBCASTED
Audiences: Everyone Is Invited
Contact: Alma Nava / Information Sciences Institute
Event Link: PER SPEAKER'S REQUEST, THIS WILL NOT BE WEBCASTED
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
NL Seminar- Farshad Kooti:Network Weirdness: Exploring the Origins of Network Paradoxes
Fri, Apr 11, 2014 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Farshad Kooti, USC/ ISI
Talk Title: Network Weirdness: Exploring the Origins of Network Paradoxes
Series: Natural Language Seminar
Abstract: Social networks have many counter-intuitive properties, including the ââ¬Åfriendship paradoxââ¬Â that states, on average, your friends have more friends than you do. Recently, a variety of other paradoxes were demonstrated in online social networks. This paper explores the origins of these network paradoxes. Specifically, we ask whether they arise from mathematical properties of the networks or whether they have a behavioral origin. We show that sampling from fat-tailed distributions always gives rise to a paradox in the mean, but not the median. We propose a strong form of network paradoxes, based on utilizing the median, and validate it empirically using data from two online social networks. Specifically, we show that for any user the majority of userââ¬â¢s friends and followers have more friends, followers, etc. than the user, and that this cannot be explained by statistical properties of sampling. Next, we explore the behavioral origins of the paradoxes by using the shuffle test to remove correlations between node degrees and attributes. We find that paradoxes for the mean persist in the shuffled network, but not for the median. We demonstrate that strong paradoxes arise due to the assortativity of user attributes, including degree, and correlation between degree and attribute.
Biography: Home Page:
http://www-scf.usc.edu/~kooti/
Host: Kevin Knight & Yang Gao
More Info: http://nlg.isi.edu/nl-seminar/
Location: 11th Flr Conf Rm # 1135, Marina Del Rey @ ISI-Info Sciences Inst.
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
AI Seminar- Virgil Griffith: Quantifying Synergy in Complex Systems
Fri, Apr 18, 2014 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Virgil Griffith, PhD from the California Institute of a Technology
Talk Title: Quantifying Synergy in Complex Systems
Abstract: Synergy is a fundamental concept in complex systems that has received much attention in computational biology. One clear application of synergistic information is in computational genetics. It is well understood that most phenotypic traits are influenced not only by single genes but by interactions among genesâ⬔for example, human eye-color is cooperatively specified by more than a dozen genes. The magnitude of this ââ¬Åcooperative specificationââ¬Â is the synergistic information between the set of genes X and a phenotypic trait Y . Another application is neuronal firings where potentially thousands of presynaptic neurons influence the firing rate of a single post-synaptic (target) neuron. Yet another application is discovering the ââ¬Åinformationally synergistic modulesââ¬Â within a complex system.
Biography: Virgil Griffith is a newly minted PhD from the California Institute of a Technology. He is now works in Silicon Valley within the cryptocurrencies space.
Home Page: http://virgil.gr
Host: Greg Ver Steeg
Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=77c09f802a064f5d8935e818a691815a1dLocation: ISI- Marina Del Rey-Conf Rm # 1135
WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=77c09f802a064f5d8935e818a691815a1d
Audiences: Everyone Is Invited
Contact: Peter Zamar
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
NL Seminar-Partitioning Networks with Node Attributes by Compressing Information Flow
Fri, Apr 25, 2014 @ 03:00 AM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Linhong Zhu, USC/ISI
Talk Title: Partitioning Networks with Node Attributes by Compressing Information Flow
Series: Natural Language Seminar
Abstract: Real-world networks are often organized as modules or communities of similar nodes that serve as functional units. These networks are also rich in content, with nodes having distinguishing features or attributes. In order to discover a network's modular structure, it is necessary to take into account not only its links but also node attributes. We describe an information-theoretic method that identifies modules by compressing descriptions of information flow on a network. Our formulation introduces node content into the description of information flow, which we then minimize to discover groups of nodes with similar attributes that also tend to trap the flow of information. The method has several advantages: it is conceptually simple and does not require ad-hoc parameters to specify the number of modules or to control the relative contribution of links and node attributes to network structure. We apply the proposed method to partition real-world networks with known community structure. We demonstrate that adding node attributes helps recover the underlying community structure in content-rich networks more effectively than using links alone. In addition, we show that our method is faster and more accurate than alternative state-of-the-art algorithms.
Biography: Linhong Zhu is currently a Postdoctoral Research Associate at Information Sciences Institute, University of Southern California, under the supervision of Dr. Kristina Lerman and Dr. Aram Galstyan. Before that, she worked as a scientist-I at Institute for Infocomm Research Singapore from Oct 2010 to Jan 2013. She got her B Eng. Degree in Computer Science from University of Science and Technology of China in 2006 (2002-2006) and received her Ph.D. Degree in Computer Engineering from Nanyang Technological University (2006-2011). Her research interests focus on large-scale social network analysis and sentiment analysis.
Home Page:http://www.isi.edu/people/linhong/research
Host: Kevin Knight & Yang Gao
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/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
ACL2014 Practice Talk: Kneser- Ney Smoothing on Expected Counts
Fri, Apr 25, 2014 @ 10:30 AM - 11:30 AM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Hui Zhang, USC/ISI
Talk Title: Kneser- Ney Smoothing on Expected Counts
Abstract: Widely used in speech and language processing, Kneser-Ney (KN) smoothing has consistently been shown to be one of the best-performing smoothing methods. However, KN smoothing assumes integer counts, limiting its potential usesâ⬔for example, inside Expectation-Maximization. In this paper, we propose a generaliza- tion of KN smoothing that operates on fractional counts, or, more precisely, on distributions over counts. We rederive all the steps of KN smoothing to operate on count distributions instead of integral counts, and apply it to two tasks where KN smoothing was not applicable before: one in language model adaptation, and the other in word alignment. In both cases, our method improves performance significantly.
Biography: Hui Zhang is a fourth year PhD student working with Professor David Chiang at the USC Information Sciences Institute. His main research interests are in statistical machine translation and machine learning.
He has focused on domain adaptation and smoothing techniques.
Home Page:
https://sites.google.com/site/zhangh1982/
Host: Yang Gao
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/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
