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144
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NIPS
1997
15 years 6 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
CORR
2006
Springer
102views Education» more  CORR 2006»
15 years 5 months ago
Theoretical Properties of Projection Based Multilayer Perceptrons with Functional Inputs
Many real world data are sampled functions. As shown by Functional Data Analysis (FDA) methods, spectra, time series, images, gesture recognition data, etc. can be processed more e...
Fabrice Rossi, Brieuc Conan-Guez
155
Voted
JLP
2006
98views more  JLP 2006»
15 years 5 months ago
Partiality I: Embedding relation algebras
As long as no cooperation between processes is supposed to take place, one may consider them separately and need not ask for the progress of the respective other processes. If a c...
Gunther Schmidt
143
Voted
IVS
2007
110views more  IVS 2007»
15 years 5 months ago
An automated approach for the optimization of pixel-based visualizations
During the last two decades, a wide variety of advanced methods for the visual exploration of large data sets have been proposed. For most of these techniques user interaction has...
Jörn Schneidewind, Mike Sips, Daniel A. Keim
179
Voted
TIT
1998
216views more  TIT 1998»
15 years 4 months ago
Data Compression and Harmonic Analysis
In this article we review some recent interactions between harmonic analysis and data compression. The story goes back of course to Shannon’s R(D) theory in the case of Gaussian...
David L. Donoho, Martin Vetterli, Ronald A. DeVore...
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