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GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
14 years 7 days ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
NN
2006
Springer
146views Neural Networks» more  NN 2006»
13 years 8 months ago
Comparison of relevance learning vector quantization with other metric adaptive classification methods
The paper deals with the concept of relevance learning in learning vector quantization and classification. Recent machine learning approaches with the ability of metric adaptation...
Thomas Villmann, Frank-Michael Schleif, Barbara Ha...
IJCNN
2000
IEEE
14 years 29 days ago
Applying CMAC-Based On-Line Learning to Intrusion Detection
The timely and accurate detection of computer and network system intrusions has always been an elusive goal for system administrators and information security researchers. Existin...
James Cannady
ICPR
2010
IEEE
13 years 12 months ago
Image Parsing with a Three-State Series Neural Network Classifier
We propose a three-state series neural network for effective propagation of context and uncertainty information for image parsing. The activation functions used in the proposed mod...
Seyed Mojtaba Seyedhosseini Tarzjani, Antonio Paiv...
ESWA
2006
154views more  ESWA 2006»
13 years 8 months ago
Artificial neural networks with evolutionary instance selection for financial forecasting
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Kyoung-jae Kim