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» On learning with dissimilarity functions
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GECCO
2003
Springer
114views Optimization» more  GECCO 2003»
14 years 2 months ago
Learning the Ideal Evaluation Function
Abstract. Designing an adequate fitness function requiressubstantial knowledge of a problem and of features that indicate progress towards a solution. Coevolution takes the human ...
Edwin D. de Jong, Jordan B. Pollack
ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
14 years 2 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
SIGIR
2004
ACM
14 years 2 months ago
Learning effective ranking functions for newsgroup search
Web communities are web virtual broadcasting spaces where people can freely discuss anything. While such communities function as discussion boards, they have even greater value as...
Wensi Xi, Jesper Lind, Eric Brill
BMCBI
2008
141views more  BMCBI 2008»
13 years 9 months ago
Functional discrimination of membrane proteins using machine learning techniques
Background: Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amin...
M. Michael Gromiha, Yukimitsu Yabuki
ADCM
2010
59views more  ADCM 2010»
13 years 9 months ago
Sampling inequalities for infinitely smooth functions, with applications to interpolation and machine learning
Sampling inequalities give a precise formulation of the fact that a differentiable function cannot attain large values, if its derivatives are bounded and if it is small on a suff...
Christian Rieger, Barbara Zwicknagl