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» A Symbolic Out-of-Core Solution Method for Markov Models
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KDD
2005
ACM
160views Data Mining» more  KDD 2005»
14 years 8 months ago
Optimizing time series discretization for knowledge discovery
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
Alfred Ultsch, Fabian Mörchen
DSN
2005
IEEE
13 years 9 months ago
Combining Response Surface Methodology with Numerical Models for Optimization of Class-Based Queueing Systems
In general, decision support is one of the main purposes of model-based analysis of systems. Response surface methodology (RSM) is an optimization technique that has been applied ...
Peter Kemper, Dennis Müller, Axel Thümml...
PE
2010
Springer
102views Optimization» more  PE 2010»
13 years 6 months ago
Extracting state-based performance metrics using asynchronous iterative techniques
Solution of large sparse linear fixed-point problems lies at the heart of many important performance analysis calculations. These calculations include steady-state, transient and...
Douglas V. de Jager, Jeremy T. Bradley
ICIP
2010
IEEE
13 years 5 months ago
Bayesian regularization of diffusion tensor images using hierarchical MCMC and loopy belief propagation
Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffus...
Siming Wei, Jing Hua, Jiajun Bu, Chun Chen, Yizhou...
ATAL
2008
Springer
13 years 9 months ago
Interaction-driven Markov games for decentralized multiagent planning under uncertainty
In this paper we propose interaction-driven Markov games (IDMGs), a new model for multiagent decision making under uncertainty. IDMGs aim at describing multiagent decision problem...
Matthijs T. J. Spaan, Francisco S. Melo