Events for June 09, 2017
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AI Seminar
Fri, Jun 09, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Dmitri Williams, USC Annenberg School for Communication
Talk Title: TAMING AND TRAINING SOCIAL DRAGONS COMBINING BIG DATA WITH SOCIAL SCIENCE IN GAMES AND BEYOND
Abstract: Organizations are hungry to leverage their data but often confused about where to begin. Most dont have theoretical frameworks or an understanding of how to apply the results in their workflow and systems. At the same time, the potential and demand for harnessing these data especially on networks and relationships have never been greater. In this talk, I will share a new technique and metric for using these data to measure the impact of people on each other for a range of applications. Validation and tests of the measure come from field work covering nearly a billion consumers, viewers, and players.
Biography: Dmitri Williams is an associate professor at the USC Annenberg School for Communication and Journalism. His research focuses on the social and economic impacts of new media, with a focus on online games. Williams was the first researcher to use online games for experiments and to undertake longitudinal research on them. He continues to study the psychology of online populations, with projects involving community, identity, sexuality, economics and machine learning. He is also the President of Ninja Metrics, a university startup focusing on big data. His work has been featured on NPR, CNN, Fox, NBC and CBS, as well as in the Economist, the New York Times, and other outlets.
Host: Mayank Kejriwal
Location: Information Science Institute (ISI) - 11th floor large conference room
Audiences: Everyone Is Invited
Contact: Kary Lau
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-Introduction to Graph Signal Processing:Tools for Harmonic Analysis on Irregular Structures
Fri, Jun 09, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Benjamin Girault , USC
Talk Title: Introduction to Graph Signal Processing: Tools for Harmonic Analysis on Irregular Structures
Series: Natural Language Seminar
Abstract: Abstract: During the past few years, graph signal processing has been extending the field of signal processing on Euclidean spaces to irregular spaces represented by graphs. We have seen successes ranging from the Fourier transform, to wavelets, vertex-frequency time frequency decomposition, sampling theory, uncertainty principle, or convolutive filtering. This presentation introduces the field, the type of signals involved, and how harmonic analysis is performed.
Biography: Benjamin Girault received his License B.Sc. and his Master M.Sc. in France from Ecole Normale Supérieure de Cachan, France, in 2009 and 2012 respectively in the field of theoretical computer science. He then received his PhD in computer science from Ecole Normale Supérieure de Lyon, France, in December 2015. His dissertation entitled Signal Processing on Graphs Contributions to an Emerging Field" focuses on extending the classical definition of stationary temporal signals to stationary graph signal. Currently, he is a postdoctoral scholar with Professors Antonio Ortega and Shri Narayanan at the University of Southern California continuing his work on graph signal processing with a focus on applying these tools to understanding human behavior.
Host: Marjan Ghazvininejad and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 6th Flr Conf Rm -# 689
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.
