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SUMMARY:IC Colloquium : Network Causal Inference in Presence of Latent Nod
 es
DTSTART:20170717T161500
DTEND:20170717T173000
DTSTAMP:20260415T082819Z
UID:17e42c31cb19a46e95a9e19bfc42e1d610cd0537701eab6a11f8337a
CATEGORIES:Conferences - Seminars
DESCRIPTION:By : Negar Kiyavash - University of Illinois\nVideo of her tal
 k\n\nAbstract :\nOne of the paramount challenges of this century is that o
 f understanding complex\, dynamic\, large-scale networks. Such high-dimens
 ional networks\, including social\, financial\, and biological networks\,
  cover the planet and dominate modern life. In this talk\, we propose nove
 l approaches to inference in such networks\, for both active (intervention
 al) and passive (observational) learning scenarios. We highlight how timin
 g could be utilized as a degree of freedom that provides rich information 
 about the dynamics. This information allows resolving direction of causati
 on even when only a subset of the nodes is observed (latent setting).  In
  the presence of large data\, we propose algorithms that identify optimal 
 or near-optimal  approximations to the topology of the network.\n\nBio :\
 nNegar Kiyavash is Willett Faculty Scholar at the University of Illinois a
 nd a joint Associate Professor of Industrial and Enterprise Engineering (I
 E) and Electrical and Computer Engineering (ECE). She is the director of A
 dvance Data Analytics Program in IE and is further affiliated with the Coo
 rdinated Science Laboratory (CSL) and the Information Trust Institute. Sh
 e received her Ph.D. degree in ECE from the University of Illinois at Urba
 na-Champaign in 2006. Her research interests are in design and analysis of
  algorithms for network inference and security. She is a recipient of NSF
  CAREER and AFOSR YIP awards and the Illinois College of Engineering Dean'
 s Award for Excellence in Research.\n\nMore information\n 
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
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