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EMO
2006
Springer
172views Optimization» more  EMO 2006»
15 years 10 months ago
Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) combines a mutation operator that adapts its search distribution to the underlying optimization prob...
Christian Igel, Thorsten Suttorp, Nikolaus Hansen
ACTAC
2006
100views more  ACTAC 2006»
15 years 6 months ago
Reconstruction of binary matrices from fan-beam projections
The problem of the reconstruction of binary matrices from their fan-beam projections is investigated here. A fan-beam projection model is implemented and afterwards employed in sy...
Antal Nagy, Attila Kuba
137
Voted
ISBI
2009
IEEE
16 years 1 months ago
Fast Algorithms for Nonconvex Compressive Sensing: MRI Reconstruction from Very Few Data
Compressive sensing is the reconstruction of sparse images or signals from very few samples, by means of solving a tractable optimization problem. In the context of MRI, this can ...
Rick Chartrand
ICASSP
2009
IEEE
16 years 1 months ago
Map approach to learning sparse Gaussian Markov networks
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
Narges Bani Asadi, Irina Rish, Katya Scheinberg, D...
ICASSP
2011
IEEE
14 years 10 months ago
Global convergence of independent component analysis based on semidefinite programming relaxation
In the independent component analysis, polynomial functions of higher order statistics are often used as cost functions. However, such cost functions usually have many local minim...
Shotaro Akaho, Jun Fujiki