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SUMMARY:Optimizing Sensing from Water to the Web
DTSTART:20100615T161500
DTSTAMP:20260406T214547Z
UID:11b1a79acf57631aaf863296d609873a1d4dda16c089b61342bc78da
CATEGORIES:Conferences - Seminars
DESCRIPTION:Andreas Krause\, California Institute of Technology\nAbstract 
 : \nWhere should we place sensors to quickly detect contamination in drink
 ing water distribution networks? Which blogs should we read to learn about
  the biggest stories on the web? These problems share a fundamental challe
 nge: How can we obtain the most useful information about the state of the 
 world\, at minimum cost?\n\nSuch sensing problems are typically NP-hard\, 
 and were commonly addressed using heuristics without theoretical guarantee
 s about the solution quality. In this talk\, I will present algorithms whi
 ch efficiently find provably near-optimal solutions to large\, complex sen
 sing problems. Our algorithms exploit submodularity\, an intuitive notion 
 of diminishing returns\, common to many sensing problems\; the more sensor
 s we have already deployed\, the less we learn by placing another sensor. 
 To quantify the uncertainty in our predictions\, we use probabilistic mode
 ls\, such as Gaussian Processes. In addition to identifying the most infor
 mative sensing locations\, our algorithms can handle more challenging sett
 ings\, where sensors need to be able to reliably communicate over lossy li
 nks\, where mobile robots are used for collecting data or where solutions 
 need to be robust against adversaries\, sensor failures and dynamic enviro
 nments.\n\nBiography :\nAndreas Krause is an assistant professor of Comput
 er Science at the California Institute of Technology. He received his Ph.D
 . from Carnegie Mellon University in 2008. Krause is a recipient of the NS
 F CAREER award and the Okawa Foundation Research Grant recognizing top you
 ng researchers in telecommunications. His research on sensor placement and
  optimized information gathering received awards at several premier confer
 ences\, as well as the best research paper award of the ASCE Journal of Wa
 ter Resources Planning and Management.
LOCATION:BC 02 https://plan.epfl.ch/?room==BC%2002
STATUS:CONFIRMED
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