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GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 1 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
CW
2008
IEEE
14 years 1 months ago
Automatic Surface Scanning of 3D Artifacts
—This paper describes an automatic 3D surface scanning technique using a 3D scanner. It allows the acquisition of a complete surface model of a 3D artifact without any manual reg...
Shiaofen Fang, Basil George, Mathew Palakal
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
13 years 11 months ago
The baldwin effect in developing neural networks
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Keith L. Downing
GECCO
2004
Springer
102views Optimization» more  GECCO 2004»
14 years 25 days ago
Dynamic and Scalable Evolutionary Data Mining: An Approach Based on a Self-Adaptive Multiple Expression Mechanism
Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving da...
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
FUIN
2011
358views Cryptology» more  FUIN 2011»
12 years 11 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...