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» Generating Data Analysis Programs from Statistical Models
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ICMLA
2007
13 years 9 months ago
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
Mingzhou (Joe) Song, Robert M. Haralick, Sté...
FLAIRS
2007
13 years 10 months ago
Mining Sequences in Distributed Sensors Data for Energy Production
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
Mehmed M. Kantardzic, John Gant
BMCBI
2006
109views more  BMCBI 2006»
13 years 7 months ago
An integrated system for genetic analysis
Background: Large-scale genetic mapping projects require data management systems that can handle complex phenotypes and detect and correct high-throughput genotyping errors, yet a...
Simon Fiddy, David Cattermole, Dong Xie, Xiao Yuan...
JORS
2010
189views more  JORS 2010»
13 years 2 months ago
Monte Carlo scenario generation for retail loan portfolios
Monte Carlo simulation is a common method for studying the volatility of market traded instruments. It is less employed in retail lending, because of the inherent nonlinearities in...
J. L. Breeden, D. Ingram
ECML
2007
Springer
14 years 1 months ago
Structure Learning of Probabilistic Relational Models from Incomplete Relational Data
Abstract. Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn...
Xiao-Lin Li, Zhi-Hua Zhou