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BMCBI
2007
207views more  BMCBI 2007»
13 years 8 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
14 years 1 months ago
SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks
Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Paulito P. Palmes, Taichi Hayasaka, Shiro Usui
IAJIT
2010
102views more  IAJIT 2010»
13 years 6 months ago
Multilayer neural network-burg combination for acoustical detection of buried objects
: A Burg technique is employed to model the long wavelength localization and imaging problem. A Burg method is used as a high resolution and stable technique. The idea of in-line h...
Mujahid Al-Azzo, Lubna Badri
FLAIRS
2008
13 years 10 months ago
The Introspective Robot: Using Self-Prediction to Improve Robot Learning
We investigate the use of self-predicting neural networks for autonomous robot learning within noisy or partially predictable environments. A benchmark experiment is performed in ...
James B. Marshall, Neil K. Makhija, Zachary D. Rot...
CEC
2009
IEEE
14 years 2 months ago
HyperNEAT controlled robots learn how to drive on roads in simulated environment
Abstract— In this paper we describe simulation of autonomous robots controlled by recurrent neural networks, which are evolved through indirect encoding using HyperNEAT algorithm...
Jan Drchal, Jan Koutník, Miroslav Snorek