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» A New Way to Introduce Knowledge into Reinforcement Learning
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ICML
2006
IEEE
16 years 18 days ago
Inference with the Universum
In this paper we study a new framework introduced by Vapnik (1998) and Vapnik (2006) that is an alternative capacity concept to the large margin approach. In the particular case o...
Fabian H. Sinz, Jason Weston, Léon Bottou, ...
GECCO
2008
Springer
121views Optimization» more  GECCO 2008»
15 years 26 days ago
Fast rule representation for continuous attributes in genetics-based machine learning
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
Jaume Bacardit, Natalio Krasnogor
3DOR
2010
14 years 6 months ago
Learning the Compositional Structure of Man-Made Objects for 3D Shape Retrieval
While approaches based on local features play a more and more important role for 3D shape retrieval, the problems of feature selection and similarity measurement between sets of l...
Raoul Wessel, Reinhard Klein
KDD
2006
ACM
123views Data Mining» more  KDD 2006»
16 years 6 days ago
Mining rank-correlated sets of numerical attributes
We study the mining of interesting patterns in the presence of numerical attributes. Instead of the usual discretization methods, we propose the use of rank based measures to scor...
Toon Calders, Bart Goethals, Szymon Jaroszewicz
INFORMATICALT
2006
88views more  INFORMATICALT 2006»
14 years 11 months ago
Improving the Performances of Asynchronous Algorithms by Combining the Nogood Processors with the Nogood Learning Techniques
Abstract. The asynchronous techniques that exist within the programming with distributed constraints are characterized by the occurrence of the nogood values during the search for ...
Ionel Muscalagiu, Vladimir Cretu