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ARTMED
2002
119views more  ARTMED 2002»
14 years 11 months ago
Lung cancer cell identification based on artificial neural network ensembles
An artificial neural network ensemble is a learning paradigm where several artificial neural networks are jointly used to solve a problem. In this paper, an automatic pathological...
Zhi-Hua Zhou, Yuan Jiang, Yu-Bin Yang, Shifu Chen
IJCNN
2007
IEEE
15 years 6 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
AAAI
2007
15 years 2 months ago
Acquiring Visibly Intelligent Behavior with Example-Guided Neuroevolution
Much of artificial intelligence research is focused on devising optimal solutions for challenging and well-defined but highly constrained problems. However, as we begin creating...
Bobby D. Bryant, Risto Miikkulainen
IJCNN
2006
IEEE
15 years 5 months ago
Improving the Convergence of Backpropagation by Opposite Transfer Functions
—The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately ...
Mario Ventresca, Hamid R. Tizhoosh
CEC
2008
IEEE
15 years 6 months ago
Neuro-evolving maintain-station behavior for realistically simulated boats
— We evolve a neural network controller for a boat that learns to maintain a given bearing and range with respect to a moving target in the Lagoon 3D game environment. Simulating...
Nathan A. Penrod, David Carr, Sushil J. Louis, Bob...