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» Approximate Inference and Constrained Optimization
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ORL
2006
105views more  ORL 2006»
13 years 7 months ago
Inventory placement in acyclic supply chain networks
The strategic safety stock placement problem is a constrained separable concave minimization problem and so is solvable, in principle, as a sequence of mixed-integer programming p...
Thomas L. Magnanti, Zuo-Jun Max Shen, Jia Shu, Dav...
AIPS
2009
13 years 8 months ago
Efficient Solutions to Factored MDPs with Imprecise Transition Probabilities
When modeling real-world decision-theoretic planning problems in the Markov decision process (MDP) framework, it is often impossible to obtain a completely accurate estimate of tr...
Karina Valdivia Delgado, Scott Sanner, Leliane Nun...
ISBI
2004
IEEE
14 years 8 months ago
Wavelet-Based fMRI Statistical Analysis and Spatial Interpretation: A Unifying Approach
Wavelet-based statistical analysis methods for fMRI are able to detect brain activity without smoothing the data. Typically, the statistical inference is performed in the wavelet ...
Dimitri Van De Ville, Thierry Blu, Michael Unser
ICIC
2009
Springer
14 years 2 months ago
Solar Radiation Forecasting Using Ad-Hoc Time Series Preprocessing and Neural Networks
In this paper, we present an application of neural networks in the renewable energy domain. We have developed a methodology for the daily prediction of global solar radiation on a ...
Christophe Paoli, Cyril Voyant, Marc Muselli, Mari...
UAI
2000
13 years 9 months ago
Adaptive Importance Sampling for Estimation in Structured Domains
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
Luis E. Ortiz, Leslie Pack Kaelbling