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GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
14 years 18 days ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski
RSS
2007
151views Robotics» more  RSS 2007»
13 years 10 months ago
Predicting Partial Paths from Planning Problem Parameters
— Many robot motion planning problems can be described as a combination of motion through relatively sparsely filled regions of configuration space and motion through tighter p...
Sarah Finney, Leslie Pack Kaelbling, Tomás ...
EUROCOLT
1999
Springer
14 years 1 months ago
Learning Range Restricted Horn Expressions
We study the learnability of first order Horn expressions from equivalence and membership queries. We show that the class of expressions where every term in the consequent of a c...
Roni Khardon
NCA
2007
IEEE
13 years 8 months ago
A data reduction approach for resolving the imbalanced data issue in functional genomics
Learning from imbalanced data occurs frequently in many machine learning applications. One positive example to thousands of negative instances is common in scientific applications...
Kihoon Yoon, Stephen Kwek
UAI
2008
13 years 10 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...