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ISMB
1993
14 years 11 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
GECCO
2009
Springer
15 years 2 months ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz
NECO
2006
157views more  NECO 2006»
14 years 9 months ago
Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression
The application of boosting technique to the regression problems has received relatively little attention in contrast to the research aimed at classification problems. This paper ...
Durga L. Shrestha, Dimitri P. Solomatine
IEEEPACT
2008
IEEE
15 years 4 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
BMCBI
2008
107views more  BMCBI 2008»
14 years 9 months ago
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
Cong Zhou, Lucas D. Bowler, Jianfeng Feng