2663 search results - page 140 / 533 » How to Choose a Timing Model |
127
Voted
IMECS
2007
15 years 7 months ago
2007
— In the globalisation spirit, one of the major objectives of companies is how to reduce the production losses cost-effectively for continuously enhancement of competitiveness an...
195
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SBRN
2000
IEEE
15 years 10 months ago
2000
IEEE
This paper proposes a simple methodology to construct an iterative neural network which mimics a given chaotic time series. The methodology uses the Gamma test to identify a suita...
170
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MICCAI
2010
Springer
15 years 4 months ago
2010
Springer
Abstract. We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accura...
165
Voted
JMLR
2010
15 years 28 days ago
2010
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
160
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BMCBI
2007
15 years 6 months ago
2007
Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over ...