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ICANN
2010
Springer
15 years 12 hour 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
ADCM
2008
187views more  ADCM 2008»
14 years 12 months ago
Approximation on the sphere using radial basis functions plus polynomials
In this paper we analyse a hybrid approximation of functions on the sphere S2 R3 by radial basis functions combined with polynomials, with the radial basis functions assumed to be...
Ian H. Sloan, Alvise Sommariva
DM
2008
86views more  DM 2008»
14 years 12 months ago
Hamiltonian properties of triangular grid graphs
A triangular grid graph is a finite induced subgraph of the infinite graph associated with the two-dimensional triangular grid. In 2000, Reay and Zamfirescu showed that all 2-conne...
Valery S. Gordon, Yury L. Orlovich, Frank Werner
ADCM
2006
133views more  ADCM 2006»
14 years 12 months ago
Convex combination maps over triangulations, tilings, and tetrahedral meshes
: In a recent paper by the first author, a simple proof was given of a result by Tutte on the validity of barycentric mappings, recast in terms of the injectivity of piecewise line...
Michael S. Floater, Valérie Pham-Trong
JMLR
2006
116views more  JMLR 2006»
14 years 11 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...