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» On the Complexity of Function Learning
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ICML
2007
IEEE
16 years 4 months ago
Classifying matrices with a spectral regularization
We propose a method for the classification of matrices. We use a linear classifier with a novel regularization scheme based on the spectral 1-norm of its coefficient matrix. The s...
Ryota Tomioka, Kazuyuki Aihara
ICML
2000
IEEE
16 years 4 months ago
Complete Cross-Validation for Nearest Neighbor Classifiers
Cross-validation is an established technique for estimating the accuracy of a classifier and is normally performed either using a number of random test/train partitions of the dat...
Matthew D. Mullin, Rahul Sukthankar
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
16 years 3 months ago
A bayesian mixture model with linear regression mixing proportions
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
104
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ICANN
2005
Springer
15 years 8 months ago
Batch-Sequential Algorithm for Neural Networks Trained with Entropic Criteria
The use of entropy as a cost function in the neural network learning phase usually implies that, in the back-propagation algorithm, the training is done in batch mode. Apart from t...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...
EUSFLAT
2007
126views Fuzzy Logic» more  EUSFLAT 2007»
15 years 4 months ago
Selecting the Optimal Rule Set Using a Bacterial Evolutionary Algorithm
In many regression learning algorithms for fuzzy rule bases it is not possible to define the error measure to be optimized freely. A possible alternative is the usage of global o...
Mario Drobics, János Botzheim, Klaus-Peter ...