BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:IC Colloquium : Machine Learning for Social Systems: Modeling Opin
 ions\, Activities and Interactions
DTSTART:20140303T161500
DTEND:20140303T173000
DTSTAMP:20260508T100855Z
UID:455f1b67a4ed977e9a96e1c40bb98f73153b96f3541c3dfdfd97cfd3
CATEGORIES:Conferences - Seminars
DESCRIPTION:By Julian McAuley\, Stanford University\nIC Faculty candidateA
 bstract\nThe proliferation of user-generated content on the web provides a
  wealth of opportunity to study humans through their online traces. I will
  discuss three aspects of my research\, which aims to model and understand
  people's behavior online. First\, I will develop rich models of opinions 
 by combining structured data (such as ratings) with unstructured data (suc
 h as text). Second\, I will describe how preferences and behavior evolve o
 ver time\, in order to characterize the process by which people "acquire t
 astes" for products such as beer and wine. Finally\, I will discuss how pe
 ople organize their personal social networks into communities with common 
 interests and interactions. These lines of research require models that ar
 e capable of handling high-dimensional\, interdependent\, and time-evolvin
 g data\, in order to gain insights into how humans behave.Bio\nJulian McAu
 ley is a postdoctoral scholar at Stanford University\, where he works with
  Jure Leskovec on modeling the structure and dynamics of social networks. 
 His current work is concerned with modeling opinions and behavior in onlin
 e communities\, especially with respect to their linguistic and temporal d
 imensions. Previously\, Julian received his PhD from the ANU under Tiberio
  Caetano\, with whom he worked on inference and learning in structured out
 put spaces. His work has been featured in Time\, Forbes\, New Scientist\, 
 and Wired\, and has received over 30\,000 "likes" on Facebook.More informa
 tion
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR