research article
Uncertainty Feature Optimization: an implicit paradigm for problems with noisy data
2011
Optimization problems with noisy data solved using stochastic programming or robust optimization approaches require the explicit characterization of an uncertainty set U that models the nature of the noise. Such approaches depend on the modeling of the uncertainty set and suffer from an erroneous estimation of the noise.
Type
research article
Web of Science ID
WOS:000290359800009
Author(s)
Date Issued
2011
Published in
Volume
57
Issue
3
Start page
270
End page
284
Editorial or Peer reviewed
REVIEWED
Written at
EPFL
EPFL units
Available on Infoscience
September 30, 2010
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