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110
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ICML
2009
IEEE
16 years 3 months ago
The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning
The purpose of this paper is three-fold. First, we formalize and study a problem of learning probabilistic concepts in the recently proposed KWIK framework. We give details of an ...
Carlos Diuk, Lihong Li, Bethany R. Leffler
118
Voted
JIFS
2002
107views more  JIFS 2002»
15 years 2 months ago
Model selection via Genetic Algorithms for RBF networks
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
Estefane G. M. de Lacerda, André Carlos Pon...
112
Voted
EC
2000
171views ECommerce» more  EC 2000»
15 years 2 months ago
Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions
Building blocks are a ubiquitous feature at all levels of human understanding, from perception through science and innovation. Genetic algorithms are designed to exploit this prev...
John H. Holland
157
Voted
IMCSIT
2010
15 years 1 days ago
Evaluation of Clustering Algorithms for Polish Word Sense Disambiguation
Word Sense Disambiguation in text is still a difficult problem as the best supervised methods require laborious and costly manual preparation of training data. Thus, this work focu...
Bartosz Broda, Wojciech Mazur
144
Voted
CIARP
2010
Springer
15 years 5 days ago
A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lod...