Sciweavers

28 search results - page 1 / 6
» Opposite Transfer Functions and Backpropagation Through Time
Sort
View
FOCI
2007
IEEE
13 years 11 months ago
Opposite Transfer Functions and Backpropagation Through Time
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Mario Ventresca, Hamid R. Tizhoosh
IJCNN
2006
IEEE
13 years 10 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
ENTCS
2008
130views more  ENTCS 2008»
13 years 4 months ago
The SPARTA Pseudonym and Authorization System
This paper deals with privacy-preserving (pseudonymized) access to a service resource. In such a scenario, two opposite needs seem to emerge. On one side, the service provider may...
Giuseppe Bianchi, M. Bonola, Vincenzo Falletta, Fr...
NIPS
1990
13 years 6 months ago
Back Propagation is Sensitive to Initial Conditions
This paper explores the effect of initial weight selection on feed-forward networks learning simple functions with the back-propagation technique. We first demonstrate, through th...
John F. Kolen, Jordan B. Pollack
TNN
2010
234views Management» more  TNN 2010»
12 years 11 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes