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BMCBI
2004
133views more  BMCBI 2004»
13 years 5 months ago
Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction
Background: RNA secondary structure prediction methods based on probabilistic modeling can be developed using stochastic context-free grammars (SCFGs). Such methods can readily co...
Robin D. Dowell, Sean R. Eddy
MICCAI
2010
Springer
13 years 3 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
ASPLOS
2006
ACM
13 years 9 months ago
Accurate and efficient regression modeling for microarchitectural performance and power prediction
We propose regression modeling as an efficient approach for accurately predicting performance and power for various applications executing on any microprocessor configuration in a...
Benjamin C. Lee, David M. Brooks
ENTCS
2007
114views more  ENTCS 2007»
13 years 5 months ago
Parametric Performance Contracts for Software Components with Concurrent Behaviour
Performance prediction methods for component-based software systems aim at supporting design decisions of software architects during early development stages. With the increased a...
Jens Happe, Heiko Koziolek, Ralf Reussner
GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
13 years 9 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon