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» Randomized Methods for Linear Constraints: Convergence Rates...
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SIAMSC
2008
179views more  SIAMSC 2008»
13 years 7 months ago
Multigrid Algorithms for Inverse Problems with Linear Parabolic PDE Constraints
Abstract. We present a multigrid algorithm for the solution of distributed parameter inverse problems constrained by variable-coefficient linear parabolic partial differential equa...
Santi S. Adavani, George Biros
INFOCOM
2007
IEEE
14 years 1 months ago
The Impact of Stochastic Noisy Feedback on Distributed Network Utility Maximization
—The implementation of distributed network utility maximization (NUM) algorithms hinges heavily on information feedback through message passing among network elements. In practic...
Junshan Zhang, Dong Zheng, Mung Chiang
TSP
2008
116views more  TSP 2008»
13 years 7 months ago
Optimal Linear Precoding Strategies for Wideband Noncooperative Systems Based on Game Theory - Part I: Nash Equilibria
In this two-part paper, we propose a decentralized strategy, based on a game-theoretic formulation, to find out the optimal precoding/multiplexing matrices for a multipoint-to-mult...
Gesualdo Scutari, Daniel Pérez Palomar, Ser...
SIAMJO
2002
77views more  SIAMJO 2002»
13 years 7 months ago
Modifying SQP for Degenerate Problems
Most local convergence analyses of the sequential quadratic programming (SQP) algorithm for nonlinear programming make strong assumptions about the solution, namely, that the activ...
Stephen J. Wright
AE
2005
Springer
14 years 1 months ago
Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies
Randomization is an efficient tool for global optimization. We here define a method which keeps : – the order 0 of evolutionary algorithms (no gradient) ; – the stochastic as...
Anne Auger, Mohamed Jebalia, Olivier Teytaud