Loading...
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
Authors
Publication date
2011
Published in
Volume
57
Issue
3
Start page
270
End page
284
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
September 30, 2010
Use this identifier to reference this record