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» Approximate Learning of Dynamic Models
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SASO
2008
IEEE
15 years 11 months ago
Self-Adaptive Dissemination of Data in Dynamic Sensor Networks
The distribution of data in large dynamic wireless sensor networks presents a difficult problem due to node mobility, link failures, and traffic congestion. In this paper, we pr...
David Dorsey, Bjorn Jay Carandang, Moshe Kam, Chri...
CVPR
2007
IEEE
16 years 6 months ago
What makes a good model of natural images?
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Yair Weiss, William T. Freeman
ICML
2008
IEEE
16 years 5 months ago
The dynamic hierarchical Dirichlet process
The dynamic hierarchical Dirichlet process (dHDP) is developed to model the timeevolving statistical properties of sequential data sets. The data collected at any time point are r...
Lu Ren, David B. Dunson, Lawrence Carin
WSC
2004
15 years 6 months ago
Function-Approximation-Based Importance Sampling for Pricing American Options
Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multi-dimensional American options. However, for many pric...
Nomesh Bolia, Sandeep Juneja, Paul Glasserman
138
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ICTAI
2003
IEEE
15 years 10 months ago
Adaptive Modeling of Biochemical Pathways
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the...
Rüdiger W. Brause