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» Convex Methods for Transduction
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CISS
2008
IEEE
15 years 4 months ago
Subgradient methods in network resource allocation: Rate analysis
— We consider dual subgradient methods for solving (nonsmooth) convex constrained optimization problems. Our focus is on generating approximate primal solutions with performance ...
Angelia Nedic, Asuman E. Ozdaglar
JDCTA
2010
272views more  JDCTA 2010»
14 years 4 months ago
Optimal Control of Nonlinear Systems Using the Homotopy Perturbation Method: Infinite Horizon Case
This paper presents a new method for solving a class of infinite horizon nonlinear optimal control problems. In this method, first the original optimal control problem is transfor...
Amin Jajarmi, Hamidreza Ramezanpour, Arman Sargolz...
ICASSP
2011
IEEE
14 years 1 months ago
Subspace pursuit method for kernel-log-linear models
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
Yotaro Kubo, Simon Wiesler, Ralf Schlüter, He...
TSP
2010
14 years 4 months ago
Methods for sparse signal recovery using Kalman filtering with embedded pseudo-measurement norms and quasi-norms
We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimiz...
Avishy Carmi, Pini Gurfil, Dimitri Kanevsky
ECML
2007
Springer
15 years 4 months 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