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» Generating Model with Uncertainty by Means of JTL
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FOCS
2005
IEEE
13 years 11 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
ANOR
2006
133views more  ANOR 2006»
13 years 5 months ago
Horizon and stages in applications of stochastic programming in finance
To solve a decision problem under uncertainty via stochastic programming means to choose or to build a suitable stochastic programming model taking into account the nature of the r...
Marida Bertocchi, Vittorio Moriggia, Jitka Dupacov...
SIGMOD
2008
ACM
169views Database» more  SIGMOD 2008»
14 years 5 months ago
MCDB: a monte carlo approach to managing uncertain data
To deal with data uncertainty, existing probabilistic database systems augment tuples with attribute-level or tuple-level probability values, which are loaded into the database al...
Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Per...
BIB
2006
69views more  BIB 2006»
13 years 5 months ago
Flux balance analysis in the era of metabolomics
Flux balance analysis (FBA) has emerged as an effective means to analyse biological networks in a quantitative manner. Much progress has been made on the extension of FBA to incor...
Jong Min Lee, Erwin P. Gianchandani, Jason A. Papi...
CSCL
2008
106views more  CSCL 2008»
13 years 5 months ago
Operationalizing macro-scripts in CSCL technological settings
: This paper presents a conceptual analysis of the technological dimensions related to the operationalization of CSCL macro-scripts. CSCL scripts are activity models that aim at en...
Pierre Tchounikine