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» On an Optimization Problem in Sensor Selection*
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CORR
2010
Springer
70views Education» more  CORR 2010»
14 years 10 months ago
Structured sparsity-inducing norms through submodular functions
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Francis Bach
IJCV
1998
157views more  IJCV 1998»
14 years 9 months ago
Stereo Matching with Nonlinear Diffusion
One of the central problems in stereo matching (and other image registration tasks) is the selection of optimal window sizes for comparing image regions. This paper addresses this ...
Daniel Scharstein, Richard Szeliski
FOGA
2011
14 years 1 months ago
The logarithmic hypervolume indicator
It was recently proven that sets of points maximizing the hypervolume indicator do not give a good multiplicative approximation of the Pareto front. We introduce a new “logarith...
Tobias Friedrich, Karl Bringmann, Thomas Voß...
MOBIHOC
2009
ACM
15 years 10 months ago
Spectrum auction framework for access allocation in cognitive radio networks
Cognitive radio networks are emerging as a promising technology for the efficient use of radio spectrum. In these networks, there are two categories of networks on different chann...
Gaurav S. Kasbekar, Saswati Sarkar
GECCO
2007
Springer
276views Optimization» more  GECCO 2007»
15 years 4 months ago
Meta-optimizing semantic evolutionary search
I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution. Distributions are not esti...
Moshe Looks