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FLAIRS
2004
13 years 11 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...
IJON
2008
116views more  IJON 2008»
13 years 10 months ago
Discovering speech phones using convolutive non-negative matrix factorisation with a sparseness constraint
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...
Paul D. O'Grady, Barak A. Pearlmutter
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 10 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
14 years 1 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
DAC
2004
ACM
14 years 11 months ago
Adaptive data partitioning for ambient multimedia
In the near future, Ambient Intelligence (AmI) will become part of everyday life. Combining feature-rich multimedia with AmI (dubbed Ambient Multimedia for short) has the potentia...
Xiaoping Hu, Radu Marculescu