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DTSTART:20190331T030000
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DTSTART:20181028T020000
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DTSTAMP:20260404T015848Z
UID:5c3c53babf1ca995474816@ist.ac.at
DTSTART:20190304T090000
DTEND:20190304T100000
DESCRIPTION:Speaker: Yuxin Chen\nhosted by Vladimir Kolmogorov\nAbstract: H
 ow can we intelligently acquire information for decision making\, when fac
 ing a large volume of data? In this talk\, I will focus on learning and de
 cision making problems that arise in robotics\, scientific discovery and h
 uman-centered systems\, and present how we can develop principled approach
 es that actively extract information\, identify the most relevant data for
  the learning tasks and make effective decisions under uncertainty. As an 
 example\, I will introduce the optimal value of information problem for de
 cision making\, and show that for a large class of adaptive information ac
 quisition problems that are known to be NP-hard\, one could devise efficie
 nt surrogate objectives that are amenable to greedy optimization\, while s
 till achieving strong approximation guarantees.I will further talk about a
  few practical challenges in real-world decision-making systems such as co
 mplex constraints\, complex action space\, and rich interfaces. More concr
 etely\, I will elaborate on how to address these practical concerns throug
 h a variety of applications\, ranging from sequential experimental design 
 for scientific discovery to interactive machine teaching for human learner
 s.
LOCATION:Mondi Seminar Room 2\, Central Building\, ISTA
ORGANIZER:tguggenb@ist.ac.at
SUMMARY:Yuxin Chen: Interactive Learning and Decision Making with Machines 
 and People
URL:https://talks-calendar.ista.ac.at/events/1757
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