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» Learning for stochastic dynamic programming
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MOR
2006
94views more  MOR 2006»
15 years 1 months ago
Conditional Risk Mappings
We introduce an axiomatic definition of a conditional convex risk mapping and we derive its properties. In particular, we prove a representation theorem for conditional risk mappi...
Andrzej Ruszczynski, Alexander Shapiro
EOR
2006
90views more  EOR 2006»
15 years 2 months ago
A parallelizable dynamic fleet management model with random travel times
In this paper, we present a stochastic model for the dynamic fleet management problem with random travel times. Our approach decomposes the problem into time-staged subproblems by...
Huseyin Topaloglu
NIPS
1993
15 years 3 months ago
Using Local Trajectory Optimizers to Speed Up Global Optimization in Dynamic Programming
Dynamic programming provides a methodology to develop planners and controllers for nonlinear systems. However, general dynamic programming is computationally intractable. We have ...
Christopher G. Atkeson
BMCBI
2011
14 years 9 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
BMCBI
2007
167views more  BMCBI 2007»
15 years 2 months ago
A stochastic differential equation model for transcriptional regulatory networks
Background: This work explores the quantitative characteristics of the local transcriptional regulatory network based on the availability of time dependent gene expression data se...
Adriana Climescu-Haulica, Michelle D. Quirk