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MP
2010
162views more  MP 2010»
13 years 4 months ago
Approximation accuracy, gradient methods, and error bound for structured convex optimization
Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...
Paul Tseng
ASC
2004
13 years 5 months ago
Solving nonconvex climate control problems: pitfalls and algorithm performances
Global optimization can be used as the main component for reliable decision support systems. In this contribution, we explore numerical solution techniques for nonconvex and nondi...
Carmen G. Moles, Julio R. Banga, Klaus Keller
CDC
2010
IEEE
13 years 24 days ago
Stochastic approximation for consensus with general time-varying weight matrices
This paper considers consensus problems with delayed noisy measurements, and stochastic approximation is used to achieve mean square consensus. For stochastic approximation based c...
Minyi Huang
ICDCS
2010
IEEE
13 years 9 months ago
Stochastic Steepest-Descent Optimization of Multiple-Objective Mobile Sensor Coverage
—We propose a steepest descent method to compute optimal control parameters for balancing between multiple performance objectives in stateless stochastic scheduling, wherein the ...
Chris Y. T. Ma, David K. Y. Yau, Nung Kwan Yip, Na...
CDC
2008
IEEE
130views Control Systems» more  CDC 2008»
14 years 7 days ago
Stochastic multiscale approaches to consensus problems
Abstract— While peer-to-peer consensus algorithms have enviable robustness and locality for distributed estimation and computation problems, they have poor scaling behavior with ...
Jong-Han Kim, Matthew West, Sanjay Lall, Eelco Sch...