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» A statistical approach to rule learning
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HIS
2008
15 years 7 months ago
Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules
Most symbolic classifiers aim at building sets of rules with good coverage and precision. While this is suitable for most applications, they tend to neglect other desirable proper...
Rafael Giusti, Gustavo E. A. P. A. Batista, Ronald...
BMCBI
2005
110views more  BMCBI 2005»
15 years 6 months ago
Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information
Background: The rapid publication of important research in the biomedical literature makes it increasingly difficult for researchers to keep current with significant work in their...
James W. Cooper, Aaron Kershenbaum
BMCBI
2006
126views more  BMCBI 2006»
15 years 6 months ago
A minimally invasive multiple marker approach allows highly efficient detection of meningioma tumors
Background: The development of effective frameworks that permit an accurate diagnosis of tumors, especially in their early stages, remains a grand challenge in the field of bioinf...
Andreas Keller, Nicole Ludwig, Nicole Comtesse, An...
NIPS
2008
15 years 7 months ago
Optimization on a Budget: A Reinforcement Learning Approach
Many popular optimization algorithms, like the Levenberg-Marquardt algorithm (LMA), use heuristic-based "controllers" that modulate the behavior of the optimizer during ...
Paul Ruvolo, Ian R. Fasel, Javier R. Movellan
UAI
2003
15 years 7 months ago
A Linear Belief Function Approach to Portfolio Evaluation
We show how to use linear belief functions to represent market information and financial knowledge, including complete ignorance, statistical observations, subjective speculations...
Liping Liu, Catherine Shenoy, Prakash P. Shenoy