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KDD
2002
ACM
138views Data Mining» more  KDD 2002»
16 years 7 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
ICASSP
2009
IEEE
16 years 1 months ago
Wildfire detection using LMS based active learning
A computer vision based algorithm for wildfire detection is developed. The main detection algorithm is composed of four sub-algorithms detecting (i) slow moving objects, (ii) gra...
B. Ugur Töreyin, A. Enis Çetin
EMO
2009
Springer
159views Optimization» more  EMO 2009»
16 years 1 months ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel
ICANN
2009
Springer
16 years 1 months ago
Measuring and Optimizing Behavioral Complexity for Evolutionary Reinforcement Learning
Model complexity is key concern to any artificial learning system due its critical impact on generalization. However, EC research has only focused phenotype structural complexity ...
Faustino J. Gomez, Julian Togelius, Jürgen Sc...
IWANN
2009
Springer
16 years 1 months ago
Optimising Machine-Learning-Based Fault Prediction in Foundry Production
Abstract. Microshrinkages are known as probably the most difficult defects to avoid in high-precision foundry. The presence of this failure renders the casting invalid, with the su...
Igor Santos, Javier Nieves, Yoseba K. Penya, Pablo...