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FLAIRS
2004
13 years 9 months ago
Iterative Improvement of Neural Classifiers
A new objective function for neural net classifier design is presented, which has more free parameters than the classical objective function. An iterative minimization technique f...
Jiang Li, Michael T. Manry, Li-min Liu, Changhua Y...
NIPS
1996
13 years 9 months ago
Radial Basis Function Networks and Complexity Regularization in Function Learning
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
Adam Krzyzak, Tamás Linder
ICANN
2010
Springer
13 years 8 months ago
Deep Bottleneck Classifiers in Supervised Dimension Reduction
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
Elina Parviainen
GRID
2006
Springer
13 years 8 months ago
Implementation of Fault-Tolerant GridRPC Applications
In this paper, a task parallel application is implemented with Ninf-G which is a GridRPC system, and experimented on, using the Grid testbed in Asia Pacific, for three months. The...
Yusuke Tanimura, Tsutomu Ikegami, Hidemoto Nakada,...
MOC
1998
66views more  MOC 1998»
13 years 7 months ago
Nonconforming finite element approximation of crystalline microstructure
Abstract. We consider a class of nonconforming finite element approximations of a simply laminated microstructure which minimizes the nonconvex variational problem for the deforma...
Bo Li, Mitchell Luskin