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Hammer, B
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Showing results 1 to 20 of 24
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Issue Date
Title
Author(s)
2004
A general framework for unsupervised processing of structured data
Hammer, B; Micheli, A; Sperduti, A; Strickert, M
2003
A note on the universal approximation capability of support vector machines
Hammer, B; Gersmann, K
2002
Architectural bias in recurrent neural networks - Fractal analysis
Tino, P; Hammer, B
2003
Architectural bias in recurrent neural networks: Fractal analysis
Tino, P; Hammer, B
2001
Closure properties of uniform convergence of empirical means and PAC learnability under a family of probability measures
Vidyasagar, M; Balaji, S; Hammer, B
2001
Generalization ability of folding networks
Hammer, B
2002
Generalized relevance learning vector quantization
Hammer, B; Villmann, T
2001
Generalized relevance LVQ for time series
Strickert, M; Bojer, T; Hammer, B
2005
Improving iterative repair strategies for scheduling with the SVM
Gersmann, K; Hammer, B
2002
Learning vector quantization for multimodal data
Hammer, B; Strickert, M; Villmann, T
2000
Learning with recurrent neural networks - Introduction
Hammer, B
2003
Neural maps in remote sensing image analysis
Villmann, T; Merenyi, E; Hammer, B
2005
New aspects in neurocomputing
Cottrell, M; Hammer, B; Villmann, T
2000
On approximate learning by multi-layered feedforward circuits
DasGupta, B; Hammer, B
2000
On the approximation capability of recurrent neural networks
Hammer, B
2005
On the generalization ability of GRLVQ networks
Hammer, B; Strickert, M; Villmann, T
2001
On the generalization ability of recurrent networks
Hammer, B
1999
On the learnability of recursive data
Hammer, B
2003
Recurrent neural networks with small weights implement definite memory machines
Hammer, B; Tino, P
2004
Recursive self-organizing network models
Hammer, B; Micheli, A; Sperduti, A; Strickert, M