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CEC
2009
IEEE
15 years 11 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
JMLR
2006
169views more  JMLR 2006»
15 years 4 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
NPL
2006
172views more  NPL 2006»
15 years 4 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
CN
2010
183views more  CN 2010»
15 years 4 months ago
A learning automata based scheduling solution to the dynamic point coverage problem in wireless sensor networks
The dynamic point coverage problem in wireless sensor networks is to detect some moving target points in the area of the network using as little sensor nodes as possible. One way ...
Mehdi Esnaashari, Mohammad Reza Meybodi
WSOM
2009
Springer
15 years 11 months ago
Incremental Figure-Ground Segmentation Using Localized Adaptive Metrics in LVQ
Vector quantization methods are confronted with a model selection problem, namely the number of prototypical feature representatives to model each class. In this paper we present a...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...