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» Stochastic MINLP optimization using simplicial approximation
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CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
13 years 3 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»
13 years 8 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»
14 years 2 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
13 years 16 days 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»
13 years 8 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...