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JMLR
2012
11 years 11 months ago
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
CORR
2006
Springer
94views Education» more  CORR 2006»
13 years 8 months ago
Fitness Uniform Optimization
Abstract-- In evolutionary algorithms, the fitness of a population increases with time by mutating and recombining individuals and by a biased selection of more fit individuals. Th...
Marcus Hutter, Shane Legg
AAAI
2012
11 years 11 months ago
Online Kernel Selection: Algorithms and Evaluations
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
GECCO
2010
Springer
254views Optimization» more  GECCO 2010»
14 years 1 months ago
Evolutionary multi-objective optimization and decision making for selective laser sintering
This paper proposes an integrated approach to arrive at optimal build orientations, simultaneously minimizing surface roughness ‘Ra’ and build time ‘T’, for object manufac...
Nikhil Padhye, Kalyanmoy Deb
CADE
2003
Springer
14 years 9 months ago
Source-Tracking Unification
We propose a practical path-based framework for deriving and simplifying source-tracking information for term unification in the empty theory. Such a framework is useful for debugg...
Venkatesh Choppella, Christopher T. Haynes