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ATMOS
2007
177views Optimization» more  ATMOS 2007»
15 years 6 months ago
Approximate dynamic programming for rail operations
Abstract. Approximate dynamic programming offers a new modeling and algorithmic strategy for complex problems such as rail operations. Problems in rail operations are often modeled...
Warren B. Powell, Belgacem Bouzaïene-Ayari
TIP
2008
133views more  TIP 2008»
15 years 4 months ago
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
Jason K. Johnson, Alan S. Willsky
CORR
2010
Springer
123views Education» more  CORR 2010»
14 years 11 months ago
Equilibria of Dynamic Games with Many Players: Existence, Approximation, and Market Structure
In this paper we study stochastic dynamic games with many players that are relevant for a wide range of social, economic, and engineering applications. The standard solution conce...
Sachin Adlakha, Ramesh Johari, Gabriel Y. Weintrau...
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ESANN
2003
15 years 6 months ago
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Fo...
QRE
2010
129views more  QRE 2010»
15 years 3 months ago
Improving quality of prediction in highly dynamic environments using approximate dynamic programming
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
Rajesh Ganesan, Poornima Balakrishna, Lance Sherry