361 search results - page 3 / 73 » Minimization of Error Functionals over Perceptron Networks |
ML
2006
ACM
13 years 9 months ago
2006
ACM
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
ICARCV
2006
IEEE
14 years 3 months ago
2006
IEEE
— Many problems in computer vision such as pose recovery and structure estimation are formulated as a minimization process. These problems vary in the use of image measurements d...
IJCNN
2006
IEEE
14 years 3 months ago
2006
IEEE
—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 ...
IJCNN
2007
IEEE
14 years 4 months ago
2007
IEEE
—A procedure is presented for selecting and ordering the polynomial basis functions in the functional link net (FLN). This procedure, based upon a modified Gram Schmidt orthonorm...
JMLR
2006
13 years 9 months ago
2006
We study some stability properties of algorithms which minimize (or almost-minimize) empirical error over Donsker classes of functions. We show that, as the number n of samples gr...