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CORR
2004
Springer
152views Education» more  CORR 2004»
13 years 8 months ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer
CORR
2002
Springer
106views Education» more  CORR 2002»
13 years 8 months ago
On model selection and the disability of neural networks to decompose tasks
A neural network with fixed topology can be regarded as a parametrization of functions, which decides on the correlations between functional variations when parameters are adapted...
Marc Toussaint
TSP
2008
166views more  TSP 2008»
13 years 8 months ago
Blind Identification of Underdetermined Mixtures by Simultaneous Matrix Diagonalization
Abstract--In this paper, we study simultaneous matrix diagonalization-based techniques for the estimation of the mixing matrix in underdetermined independent component analysis (IC...
Lieven De Lathauwer, Joséphine Castaing
AAAI
2008
13 years 11 months ago
HTN-MAKER: Learning HTNs with Minimal Additional Knowledge Engineering Required
We describe HTN-MAKER, an algorithm for learning hierarchical planning knowledge in the form of decomposition methods for Hierarchical Task Networks (HTNs). HTNMAKER takes as inpu...
Chad Hogg, Héctor Muñoz-Avila, Ugur ...
JCSS
2008
81views more  JCSS 2008»
13 years 9 months ago
A simulator for adaptive parallel applications
Dynamically allocating computing nodes to parallel applications is a promising technique for improving the utilization of cluster resources. Detailed simulations can help identify...
Basile Schaeli, Sebastian Gerlach, Roger D. Hersch