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» Algorithm Selection using Reinforcement Learning
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IEEECIT
2007
IEEE
15 years 9 months ago
An Experimental Study on Feature Subset Selection Methods
In the field of machine learning and pattern recognition, feature subset selection is an important area, where many approaches have been proposed. In this paper, we choose some fe...
Chulmin Yun, Donghyuk Shin, Hyunsung Jo, Jihoon Ya...
IJCNN
2006
IEEE
15 years 9 months ago
C2FS: An Algorithm for Feature Selection in Cascade Neural Networks
Wrapper-based feature selection is attractive because wrapper methods are able to optimize the features they select to the specific learning algorithm. Unfortunately, wrapper met...
Lars Backstrom, Rich Caruana
ECML
2005
Springer
15 years 8 months ago
Natural Actor-Critic
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
Jan Peters, Sethu Vijayakumar, Stefan Schaal
IJCNN
2006
IEEE
15 years 9 months ago
Dynamic Hyperparameter Scaling Method for LVQ Algorithms
— We propose a new annealing method for the hyperparameters of several recent Learning Vector Quantization algorithms. We first analyze the relationship between values assigned ...
Sambu Seo, Klaus Obermayer
GECCO
2010
Springer
155views Optimization» more  GECCO 2010»
15 years 8 months ago
Negative selection algorithms without generating detectors
Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
Maciej Liskiewicz, Johannes Textor