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» On the Complexity of Function Learning
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IJCNN
2008
IEEE
15 years 7 months ago
Numerical condition of feedforward networks with opposite transfer functions
— Numerical condition affects the learning speed and accuracy of most artificial neural network learning algorithms. In this paper, we examine the influence of opposite transfe...
Mario Ventresca, Hamid R. Tizhoosh
87
Voted
DAGSTUHL
1994
15 years 2 months ago
Function-Based Object Recognition
Functionality-based recognition systems recognize objects at the category level by reasoning about how well the objects support the expected function. Such systems naturally assoc...
Louise Stark, Kevin W. Bowyer
71
Voted
GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
15 years 6 months ago
Alternative implementations of the Griewangk function
The well-known Griewangk function, used for evaluation of evolutionary algorithms, becomes easier as the number of dimensions grows. This paper suggests three alternative implemen...
Artem Sokolov, L. Darrell Whitley, Monte Lunacek
103
Voted
ISMVL
2002
IEEE
82views Hardware» more  ISMVL 2002»
15 years 5 months ago
Representations of Logic Functions Using QRMDDs
This paper considers quasi-reduced multi-valued decision diagrams with bits (QRMDD( )s) to represent twovalued logic functions. It shows relations between the numbers of nodes in ...
Shinobu Nagayama, Tsutomu Sasao, Yukihiro Iguchi, ...
94
Voted
ENTCS
2008
124views more  ENTCS 2008»
15 years 24 days ago
Modular Functional Descriptions
The construction of reactive systems often requires the combination of different individual functionalities, thus leading to a complex overall behavior. To achieve an efficient co...
Bernhard Schätz