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» Stochastic MINLP optimization using simplicial approximation
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CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
14 years 6 months ago
Aggregation-based model reduction of a Hidden Markov Model
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Kun Deng, Prashant G. Mehta, Sean P. Meyn
ANOR
2006
59views more  ANOR 2006»
14 years 12 months ago
The empirical behavior of sampling methods for stochastic programming
Abstract. We investigate the quality of solutions obtained from sample-average approximations to two-stage stochastic linear programs with recourse. We use a recently developed sof...
Jeff Linderoth, Alexander Shapiro, Stephen Wright
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 5 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
ICASSP
2011
IEEE
14 years 3 months ago
Multicast transmit beamforming using a randomize-in-time strategy
Recently there has been much interest in using transmit beamforming to provide multi-antenna physical-layer multicasting. A state of the art in this context is the semidefinite r...
Sissi X. Wu, Wing-Kin Ma
MP
2002
93views more  MP 2002»
14 years 11 months ago
Conditioning of convex piecewise linear stochastic programs
In this paper we consider stochastic programming problems where the objective function is given as an expected value of a convex piecewise linear random function. With an optimal s...
Alexander Shapiro, Tito Homem-de-Mello, Joocheol K...