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PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Network Inference: from Passive to Active Learning
DTSTART:20191112T161500
DTEND:20191112T171500
DTSTAMP:20260501T103724Z
UID:1fc7a52e31a3b00d00f34c367868681293dfdf1f92ab13a834a440a5
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Negar Kiyavash\, Chair of Business Analytics\, EPFL\n\n
  \n\n\nOne of the paramount challenges of this century is that of underst
 anding complex\, dynamic\, large-scale networks. Such high-dimensional net
 works\, including social\, financial\, and biological networks\, cover the
  planet and dominate modern life. In this talk\, we propose novel approach
 es to inference in such networks\, for both active (interventional) and pa
 ssive (observational) learning scenarios. We highlight how timing could be
  utilized as a degree of freedom that provides rich information about the 
 dynamics. This information allows resolving direction of causation even wh
 en only a subset of the nodes is observed (latent setting).  In the prese
 nce of large data\, we propose algorithms that identify optimal or near-op
 timal  approximations to the topology of the network.
LOCATION:INM 203 https://plan.epfl.ch/?room==INM%20203
STATUS:CONFIRMED
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