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MP
2002
195views more  MP 2002»
13 years 6 months ago
Nonlinear rescaling vs. smoothing technique in convex optimization
We introduce an alternative to the smoothing technique approach for constrained optimization. As it turns out for any given smoothing function there exists a modification with part...
Roman A. Polyak
ECML
2007
Springer
14 years 27 days ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
ICASSP
2011
IEEE
12 years 10 months ago
Bounded gradient projection methods for sparse signal recovery
The 2- 1 sparse signal minimization problem can be solved efficiently by gradient projection. In many applications, the signal to be estimated is known to lie in some range of va...
James Hernandez, Zachary T. Harmany, Daniel Thomps...
GECCO
2007
Springer
142views Optimization» more  GECCO 2007»
14 years 27 days ago
Improving global numerical optimization using a search-space reduction algorithm
We have developed an algorithm for reduction of search-space, called Domain Optimization Algorithm (DOA), applied to global optimization. This approach can efficiently eliminate ...
Vinicius Veloso de Melo, Alexandre C. B. Delbem, D...
SIAMMAX
2010
156views more  SIAMMAX 2010»
13 years 1 months ago
Preconditioned Conjugate Gradient Method for Optimal Control Problems with Control and State Constraints
Optimality systems and their linearizations arising in optimal control of partial differential equations with pointwise control and (regularized) state constraints are considered. ...
Roland Herzog, Ekkehard W. Sachs